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DEBRE BERHAN UNIVERSITY COLLEGE OF COMPUTING Minimum Threshold Value Based Jellyfish Periodic Drop Attack Detection Algorithm (MTV-JPDADA) for Mobile Ad Hoc Networks (MANETs) A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master Of Sciences in Computer Networking and Security Dawit Seyifu Woldehanna Debre Berhan, Ethiopia JUNE 2011 E.C.

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Page 1: DEBRE BERHAN UNIVERSITY COLLEGE OF COMPUTING …

DEBRE BERHAN UNIVERSITY

COLLEGE OF COMPUTING

Minimum Threshold Value Based Jellyfish Periodic

Drop Attack Detection Algorithm (MTV-JPDADA)

for Mobile Ad Hoc Networks (MANETs)

A Thes is Submit ted in Part ia l Fu l f i l lment of the Requirements

for the Degree o f Master Of Sc iences in Computer Netw orking

and Secur i ty

Dawit Seyifu Woldehanna

Debre Berhan, Ethiopia

JUNE 2011 E.C.

Page 2: DEBRE BERHAN UNIVERSITY COLLEGE OF COMPUTING …

DEBRE BERHAN UNIVERSITY

COLLEGE OF COMPUTING

DEPARTMENT OF INFORMATION TECHNOLOGY

Minimum Threshold Value Based Jellyfish Periodic

Drop Attack Detection Algorithm (MTV-JPDADA)

for Mobile Ad Hoc Networks (MANETs)

A Thes is Submit ted in Part ia l Fu l f i l lment of the Requirements

for the Degree o f Master Of Sc iences in Computer Netw orking

and Secur i ty

Dawit Seyifu Woldehanna

Advisor: Samuel Asferaw (Ph.D.)

Debre Berhan, Ethiopia

JUNE 2011 E.C.

Page 3: DEBRE BERHAN UNIVERSITY COLLEGE OF COMPUTING …

Approval Page

T hi s M .S c . t h es i s p r op os a l en t i t l ed w i t h “ Min im um Thr e s ho l d V a l u e

Bas ed J e l l yf i s h Pe r io d i c Dr op At t ack D et ec t i on Algo r i t hm (M T V -

J PD A DA ) fo r M ob i l e Ad Ho c N et wo rks (M A NE Ts ) ” h a s been ap p ro v ed

b y t h e f o l l ow in g ex amin e rs a f t e r t he p r e s en t a t io n f o r t h e d egr ee o f

M as t e r o f S c i en ce in C om put e r N e t w ork in g and S ecu r i t y .

A d v i s o r :

1 . S AM UE L A S F E R AW ( P h . D . ) S i gn _ _ _ _ _ _ _ _ _ _ _ _ Da t e _ _ _ _ _ _ _ _ _ _ _

M e m b e r s o f t h e E x a m i n i n g b o a r d :

1 . _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ S i g n _ _ _ _ _ _ _ _ _ _ _ _ Da t e _ _ _ _ _ _ _ _ _ _ _

2 . _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ S i g n _ _ _ _ _ _ _ _ _ _ _ _ Da t e _ _ _ _ _ _ _ _ _ _ _

3 . _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ S i g n _ _ _ _ _ _ _ _ _ _ _ _ Da t e _ _ _ _ _ _ _ _ _ _ _

Page 4: DEBRE BERHAN UNIVERSITY COLLEGE OF COMPUTING …

Dedicat ion

T hi s Th es i s Wo r k

i s

D ed i ca t ed

t o

M y Fam i l y.

D aw i t Se yi f u

Page 5: DEBRE BERHAN UNIVERSITY COLLEGE OF COMPUTING …

Debre Berhan Universi ty

College of Computing

Department of Information Technology

A Copy right Sta tement

B y m y s i gn a tu r e be l ow , I d ec l a r e and a f f i r m th a t t h i s t h es i s i s

m y w o r k . I h av e fo l l ow ed a l l e t h i ca l p r i n c i p l es o f s ch o l a r s h i p in t he

p r ep ar a t io n , ex p e r im en t an d A l gor i thm d es i gn , s i mul a t io n an a l ys i s an d

co mpl e t io n o f t h i s t h es i s . A l l s cho l a r ly m a t t e r t h a t i s i nc l ud ed in t h e

t h es i s h a s b een g iven r eco gn i t i on t h rou gh c i t a t i on . I a f f i r m t h a t I h av e

c i t ed and re f e r en ced a l l s ou r ces u s ed i n t h i s do cum en t . E v e r y s e r i ous

e f f o r t h as b een m ad e t o av o i d an y p l ag i a r i sm i n t h e p r epa r a t i on o f t h i s

t h es i s .

T h i s t h es i s i s s ubmi t t ed i n pa r t i a l f u l f i l lm en t o f t h e r eq u i r em en t

f o r a d egr ee f r om t h e C o l l ege o f C om pu t in g S c i en ce in D eb r e Be r h an

U n iv e rs i t y . T h e t he s i s i s d epo s i t ed in t h e D eb r e Be rh an Un iv e rs i t y

Li b r a r y an d i s m ad e ava i l ab l e t o bo r r o w er s u nd e r t he r u l e s o f t h e

l i b r a r y. I s e r i ous l y d ec l a r e t h a t t h i s t h e s i s h as n o t b een s u bmi t t ed t o

an y o t h e r i n s t i t u t io n an yw h e r e f o r t h e aw a r d o f an acad emi c d egr ee ,

d ip lom a o r c e r t i f i ca t e .

D ec la red By :

N am e: __ __ __ __ __ __ _ __ __ _ S i gn : __ __ __ __ __ __ _ __ __ _

D a t e : _ __ __ __ __ ___ _ __ _ _

C onf i rmed by ad v i s o r :

N am e: __ __ __ __ __ __ _ __ __ _ S i gn : __ __ __ __ __ __ _ __ __ _

D a t e : _ __ __ __ __ ___ _ __ _ _

Page 6: DEBRE BERHAN UNIVERSITY COLLEGE OF COMPUTING …

vi

Abstract

M ob i l e ad h o c ne tw o r k (M A NE T) i s a t yp e o f w i r e l e s s n e t wo r k t ha t

o p e r a t es w i th ou t d ed i ca t ed ne tw o rk i n f r as t r u c tu r e . Th i s k i nd o f

n e tw o rk d o es n o t hav e a m ech an i sm to de t ec t m al i c i ou s u s e r s . Du e t o

h i gh v u ln e r ab i l i t i e s i n mo b i l e ad -h o c n e t w or ks , n od es cou ld be

ex po s ed to a t t acks b y m a l i c i ou s n odes . T h i s r es ea rch s tu d y f o cu s e s

s p ec i f i c a l l y o n d e t ec t i n g J e l l yf i s h p e r i od i c d r op a t t a ck i n M o bi l e Ad

H o c N et wo r k . Th e m ai n p u rp os e o f t he J e l l yf i s h p e r io d ic d r op a t t ack

i s t o d r op th e p ack e t s en t t o t h e d es t in a t io n n od e . T hus , t h e ne tw o rk

p e r f o r man ce w ou l d d egr ad e and w eaken t h e n e t wo rk r eso u r ces su ch as

co mp ut i n g po w er an d b an dw id t h co ns i d er ab l y d ec l in e , w h ich l e ad t he

n e tw o rk t o b e ge t t i n g w o rs e . Th i s t hes i s s tu d y an a l yz ed t h e e f f ec t s o f

t h e J e l l yf i s h p e r iod i c d r op a t t a ck on m ob i l e A d H oc n e tw o r k b a sed on

A d ho c on - dem and d i s t an ce v ec to r ( A O D V ) . Th e s i mul a t io n i s

p e r f o r med on th e b a s i s o f pe r f o r m an ce p a ram et e r s and i t s e f f ec t i s

an a l yz ed a f t e r add in g J e l l yf i s h pe r i od ic d r op a t t a ck n o d es in t h e

n e tw o rk . T h e P e r fo r man ce o f ou r m in i mum th r es ho ld v a l u e b a sed

J e l l yf i s h p e r i od i c d r op a t t a ck d e t ec t io n a l go r i t hm sh ows t h a t 80 .3 3 %

d e t ec t i on r a t e . Hen ce , an o t h er en han cem en t l i ke P ack e t D e l i v e r y

R a t io , Av e r age En d - t o - E nd D el a y, an d N e tw o rk Th r ou gh pu t , a r e

i mp ro v ed b y 1 2 .4 0% , 5 1 . 13 % , and 1 .94 % , r es p ec t i v e l y.

Keyw o rds : Mi nimu m Th r es ho l d V a l u e (M TV ) , At t ack D e tec t io n ,

A O D V, M ob i l e Ad - H o c N et w or ks , J e l l yf i s h P e r i od i c D rop

A t t ack , v u ln e r ab i l i t i e s , m a l i c io us n odes

Page 7: DEBRE BERHAN UNIVERSITY COLLEGE OF COMPUTING …

vii

Acknowledgments

Fi r s t , I w o u ld l i k e to t h an k a lmi gh t y ( G O D) wh o gave m e t h e po w er ,

p a t i en ce , h ea l th , en v i r onm ent , an d peo p l e t o s up po r t m e d ur in g m y

t h es i s s t ud y, and b l e s s ed m e in com pl e t in g t h i s r es ea r ch .

In ad d i t i o n , I w o u ld l i k e to ex pr e s s m y d eep es t g r a t i t ud e t ow ar ds m y

A d v i s o r , D r . S am ue l As f e r aw , f o r a l l h i s ad v i ce , v a l uab l e su pp or t ,

gu i d an ce , co ns t r u c t iv e com ment s , p a t i en ce , k i nd en cou ragem en t , t im e

an d k no wl ed ge , wh i ch h e p ro v i d ed d ur i n g m y s t ud y an d w i t ho u t wh i ch

I w o u l d n ev e r h av e r each ed th i s s t age .

D aw i t Se yi f u

Page 8: DEBRE BERHAN UNIVERSITY COLLEGE OF COMPUTING …

viii

Abbreviations

A C K A ck no wl ed gm ent

A O D V A d h o c On - D em an d D i s t an ce V ec to r

BM T Beh av i o ra l Mo ni t o r i n g T ab l e

C BR C on s t an t B i t Ra t e

D C D r o p C ou n t

D O S D en i a l o f S e rv i ce

D SR D yn am i c So u rce Ro u t in g

D s t D es t in a t io n No d e

D T D T r us t - b as ed D et ec t io n

E 2 E E n d t o end

F IFO F i r s t i n F i r s t Ou t

FJ A D A Fr i end sh i p J e l l yf i sh At t ack D et ec t i on A l go r i t hm

FN R Fa l s e N ega t iv e R a te

FPR Fa l s e P os i t i ve R a t e

FT F r i end sh i p t ab l e

FT P F i l e Tr ans f e r P r o t oco l

G B G i ga Bi t e

G Hz G i gah e r t z

G RP G eo gr aph i c R ou t ing P ro to co l

H T TP H yp e r T ex t T r an spo r t P r o to co l

I / P In t e r n e t P r o t o co l

J F J e l l yf i s h

J PD A DA J e l l yf i s h P e r i od i c d r o p At t ack d e t ec t i on a l go r i thm

M AC M edi a A cces s C on t r o l

M A NE Ts M ob i l e A d ho c N etw o r k

M S M on i t o r in g S tep

M T M a l i c i ous Tab l e

M T V M in imu m Th r es ho ld V a lu e

N S2 N e t wo rk S i mul a to r 2

N S3 N e t wo rk S i mul a to r 3

N S N N ex t S uccess o r Nod e

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ix

O t c l O b jec t t c l

P D F P ack e t D e l i v e r y f r ac t i on

P DR P ack e t D e lv e r R a t io n

P FN P ack e t Fo rw ard e r N o d e

Q oS Q u a l i t y- o f - S e r v i ce

R AM R and om A cces s con t ro l

R ERR R ou te E r r o r

R T O R et r ansm iss io n T im eou t

S r c S ou r ce No d e

T C L T o o l Com m an d Lan gu age

T CP T r ansm is s io n Co n t ro l P r o t oco l

T O RA T emp o ra r i l y O r d e r ed R ou t in g P r o to co l

T r 1 T h r es ho ld V a l u e 1

U D P U s e r D a t ag r am P r o t o co l

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Table of Contents

Abstract ................................................................................................................................... vi

Abbreviations ........................................................................................................................ viii

List of Tables ......................................................................................................................... xii

List of Figures ....................................................................................................................... xiii

Chapter 1 Introduction ............................................................................................................. 1

1.1 Research Background .................................................................................................... 1

1.1.1 Mobile Ad-hoc Networks (MANET) ...................................................................... 3

1.1.2 Challenge in MANETS ........................................................................................... 4

1.1.3 Types of Attack in MANET Based On Performance .............................................. 6

1.1.4 Jellyfish Attack ........................................................................................................ 7

1.2 Problem Statement ....................................................................................................... 10

1.3 Research Objectives ..................................................................................................... 11

1.3.1 General Objective .................................................................................................. 11

1.3.2 Specific Objectives ................................................................................................ 11

1.4 Scope and Limitation ................................................................................................... 12

1.5 Methodology ................................................................................................................ 12

1.5.1 Literature Review and Related Works .................................................................. 12

1.5.2 Tools and Simulator .............................................................................................. 12

1.5.3 Prototyping ............................................................................................................ 13

1.6 The Significance of the Study ...................................................................................... 13

1.7 Thesis Organization ..................................................................................................... 13

Chapter 2 Related Works ....................................................................................................... 14

2.1 Related Works .............................................................................................................. 14

2.2 Summary ...................................................................................................................... 19

Chapter 3 Minimum Threshold Value Based Jellyfish Periodic Drop Attack Detection

Algorithm (MTV-JPDADA) ................................................................................................. 20

3.1 Drop Count Calculation ............................................................................................... 20

3.2 Minimum Threshold Value (MTV) ............................................................................. 20

3.3 Proposed Model ........................................................................................................... 21

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Chapter 4 Implementation and Performance Evaluation ....................................................... 31

4.1 Implementation and Performance Metrics Analysis .................................................... 31

4.1.1 Attack Detection Rate ........................................................................................... 31

4.1.2 False Negative Rate (FNR) ................................................................................... 31

4.1.3 False Positive Rate (FPR)...................................................................................... 31

4.1.4 Average End-to-End Delay ................................................................................... 32

4.1.5 Packet Delivery Ratio (Fraction) ........................................................................... 32

4.1.6 Throughput ............................................................................................................ 32

4.2 Simulation Tools .......................................................................................................... 32

4.2.1 NS2 ........................................................................................................................ 33

4.2.2 Eclipses .................................................................................................................. 34

4.2.3 GNU Plot ............................................................................................................... 35

4.2.4 Aho, Weinberger, and Kernighan Scripts ............................................................. 35

4.2.5 NSG2.1 .................................................................................................................. 36

4.3 Results and Discussions ............................................................................................... 36

4.3.1 Experimental Design and Scenario for Jellyfish Periodic Drop Attack ................ 36

4.3.2 Results and Evaluations against Jellyfish Periodic Drop Attacks ......................... 39

4.3.3 Experimental Design and Scenario for MTV-JPDADA ....................................... 40

4.3.4 Results and Evaluations against Minimum Threshold Value based Jellyfish

Periodic Drop Attack Detection Algorithm (MTV-JPDADA) ............................... 42

Chapter 5 Conclusion and Future work ................................................................................. 47

5.1 Conclusion ................................................................................................................... 47

5.2 Future Work ................................................................................................................. 48

References .............................................................................................................................. 50

Appendix ................................................................................................................................ 54

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List of Tables

TABLE 2.1 RELATED WORKS SUMMARY ................................................................................... 19

TABLE 3.1 FRIENDSHIP TABLE (FT) .......................................................................................... 23

TABLE 3.2 MALICIOUS TABLE (MT) .......................................................................................... 23

TABLE 3.3 BEHAVIOR MONITORING TABLE (BMT) .................................................................... 24

TABLE 4.1 SIMULATION PARAMETERS ..................................................................................... 36

TABLE 4.2 ANALYSIS TABLE OF DETECTION RATE ................................................................... 43

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List of Figures

FIGURE 1.1 AD HOC NETWORKS [28] ......................................................................................... 3

FIGURE 1.2 CHALLENGES IN MANET [28] ................................................................................... 6

FIGURE 1.3 JELLYFISH REORDER ATTACK [14] .......................................................................... 8

FIGURE 1.4 JELLYFISH DELAY VARIANCE ATTACK [14] ............................................................. 9

FIGURE 1.5 JELLYFISH PERIODIC DROP ATTACK [14] ............................................................... 10

FIGURE 3.1 PROPOSED MTV-JPDADA FLOW CHART................................................................... 27

FIGURE 4.1 AODV WITH 25 NORMAL NODES ............................................................................ 38

FIGURE 4.2 AODV 25 NODES WITH JPD ATTACK ....................................................................... 38

FIGURE 4.3 AVERAGE THROUGHPUT OF MANETS ..................................................................... 39

FIGURE 4.4 PACKET DELIVERY RATIO ...................................................................................... 40

FIGURE 4.5 AODV WITH ATTACK ............................................................................................. 41

FIGURE 4.6 DETECTION RATE OF MTV-JPDADA ........................................................................ 43

FIGURE 4.7 FALSE NEGATIVE RATE OF MTV-JPDADA ................................................................ 44

FIGURE 4.8 FALSE POSITIVE RATE OF MTV-JPDADA .................................................................. 44

FIGURE 4.9 END TO END DELAY OF MTV-JPDADA ..................................................................... 45

FIGURE 4.10 PACKET DELIVERY RATIO OF MTV-JPDADA .......................................................... 46

FIGURE 4.11 AVERAGE THROUGHPUT ...................................................................................... 46

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Chapter 1 Introduction

1 .1 Research Background

M ob i l e Ad H o c n e tw o rk s ( MA N ET s ) a r e d i s t i n gu i s h ed b y t h e i r

au to nom ou s n a t u re an d th e l a ck o f a cen t r a l au t ho r i t y . E v e r y d ev ice i s

f r e e t o mo ve s ep a ra t e l y , c au s es d yn a m ic to po lo g y o f t he M A NE T . A

m aj o r d i f f i cu l t y i n M A NE T i s t o m ai n t a i n i n fo r ma t io n n eed ed t o r ou te

t r a f f i c e f f i c i en t l y [ 1 ] .

M ob i l e Ad - Ho c N et w or ks ( MA N ET ) us u a l l y m ad e u se in s ev e ra l a rea s

an d in d i v id u a l s ' l i f e app l i c a t i on s , f o r ex am pl e , e a r th m on i to r i n g ,

d i s a s t ro us even t an t i c ip a t io n , f a rmi n g b io m ed i ca l r e l a t ed ap p l i c a t io ns ,

an d nu mer ou s d i f fe r en t a r ea s . T h e s ecu r i t y t h r ea t i s o ne o f t h e m aj o r

ch a l l en ges i n MA NE T , a s i t i s o n e o f t h e p r im a r y f u n d am ent a l s o f t h e

w i r e l es s s en so r n e t w or k , ye t t h i s i s s u e h as n o t b een s a t i s f ac to r i l y

i nv es t i ga t ed [ 2 ] .

S ecu r i t y i n M ob i l e A d - Ho c N et wo rk i s t h e m os t v e r y i m p o r t an t w o r r y

f o r t h e e s s en t i a l ex i s t en ce o f t h e n e t wo r k . T he acce s s ib i l i t y o f

n e tw o rk s e rv i ce s , co n f id en t i a l i t y , an d i n t eg r i t y o f t h e d a t a c an b e

accom pl i sh ed b y gu a r an t ee i n g s ecu r i t y i s s u es . MA N ET s f requ en t l y

f ami l i a r t h e t h r ea t e f f ec t s o f s ecu r i t y a s s au l t s o n acco un t o f i t s f e a t u r e

l i k e op en m ed i um , ch an g i n g i t s t op o l o g y p o w er f u l l y , t h e ab s en ce o f

f o ca l s u rv e i l l an ce an d adm in i s t r a t i on , s a t i s f yi n g a l go r i thm s and no

c l ea r d e f en s e m echan i sm . T h es e co mpo n en t s h av e ch an ged th e co mb at

zo n e con d i t i o n fo r t h e MA N ET s aga ins t s ecu r i t y t h r ea t s [ 2 ] .

T h e M A NE Ts wo r k n o t i n c l ud i n g a n in t eg r a t ed o r gan iz a t i on wh e r e t he

n o des comm uni ca t e w i t h on e ano the r b a s ed on m utua l t rus t . T h i s

ch a r ac t e r i s t i c m akes M A NE Ts m o re s us cep t i b l e and exp lo i t ed b y an

a t t a ck er i n s id e th e n e t w or k . Wi r e l es s co nn ec t io ns i n t h e s ame w a y

m ak e th e M A NE Ts m o re su s cep t ib l e t o t h e a t t a ck e r , w h i ch m ak e i t l e s s

ch a l l en g i n g f o r t h e a t t a ck e r t o go i ns i d e th e n e t w or k and ga in access

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2

t o t h e p r o gr es s ing co r r e sp on d en ce . Becau s e m ob i l e n o des p r e sen t

i n s i d e th e r an ge o f w i r e l e s s co nn ec t io n can ov e rh ea r a n d ev en

p a r t i c ip a t e i n t h e ne t wo r k [ 2 ] .

M A NE Ts mu s t hav e a p ro t ec t ed p a th w ay f o r t r ans mis s i on and

co mmu ni ca t io n an d t h i s i s a r e a l l y h a r d and imp o r t an t ma t t e r a s t h e re

a r e r a i s i n g t h rea t s o f a t t a ck o n mo bi l e n e t wo r ks . Secu r i t y i s t h e

r eq u i r em en t o f t h e d a y. W i t h an un am bi gu ou s en d go a l t o g iv e s ecu re

co mmu ni ca t io n and t r an smi ss i on , t he a r ch i t e c t m us t r e a l i z e un iq ue

k in ds o f a t t a ck s and t h e i r cons equ en ces f o r t h e M AN ET s . S yb i l a t t a ck ,

Wo rm h ol e a t t ack , f l o od i n g a t t a ck , r ou t in g t ab l e o ve r f lo w a t t a ck ,

D en i a l o f S e r v i ce ( D OS ) , i mp e rs ona t i on a t t ack , J e l lyf i s h a t t ack ,

s e l f i s h n od e mi sb eh av i n g , Bl ack ho le a t t a ck a r e t h e k in d o f a t t a cks

t h a t a M AN E T can su f f e r f ro m. A M A NE T i s mo r e o p en to t h ese

ca t ego r i es o f a t t a ck s b ecau se co mmun i ca t i on i s b a s ed on m ut u a l t r us t

b e tw een t h e no d es , t h e r e i s no mi dd le p o in t f o r n e t wo r k m an agem ent ,

n o au th or i z a t i on fac i l i t y , d yn am i ca l ly ch an g i n g t op o l og y an d l i mi t ed

r e s ou r ces [ 1 ] [ 2 ] .

J e l l yf i s h a t t a ck i s o f t h r ee t yp es , nam el y J e l l yf i s h p ack e t d ro pp i n g

a t t a ck ; J e l l yf i s h d e l ay v a r i ance a t t a ck , an d t h e J e l l yf i s h p ack e t

r eo r de r i n g a t t a ck . E ach k i nd o f J e l l yf i sh a t t a ck d egr ades t h e pu b l i c

l oo k o f t h e ne tw or k b y l e av in g ou t o r a l t e r i n g t h e seq u en ce o f t he

p ack e t o r b y d e l a yi n g th e ackn o wl ed gm ent [ 1 ] [ 2 ] .

T h e J e l l yf i s h a t t ack i s a on e t yp e o f t h e den i a l o f s e rv i ce a t t ack th a t

u s es a p as s i v e app ro ach w hi ch i s d i f f i cu l t t o f i nd i t . I t p r o du ces d e l a y

b e f o re t h e t r ansm i t t a l an d r ecep t i on o f d a t a b un d l es i n t h e n e t w or k .

A p p l i c a t io ns su ch a s H TT P, FTP and v id eo co n f e r en c in g a r e p r ov id ed

b y T C P and U DP. J e l l yf i s h a t t a ck d i s tu r bs t h e fu n c t i on in g o f bo th

p r o t oco l s . I t i s t h e s am e a s t h e b l ack h o l e a t t a ck , bu t t he d i f f e r en ce i s

t h a t t h e b l ack h o l e a t t ack e r n od e d r op s a l l t h e d a t a p ack e t s bu t

J e l l yf i s h a t t ack e r n o de p ro du ces de l a y d u r i n g fo r w a rd i n g pack e t s .

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J e l l yf i s h a t t a ck s a re t a r ge t ed aga in s t c l os ed lo op f lo ws . T CP has w e l l -

k n ow n v u l n er ab i l i t i e s t o d e l a y, d r o p an d d i s o rd e r t h e pack e t s . D u e t o

t h es e n od es can chan ge th e s eq ue n ce o f t h e p acke t s a l s o d r op som e o f

t h e d a t a p ack e t s? T h e J e l l yf i s h a t t a ck e r no d es f u l l y o b e y p r o to co l

r u l e s ; h ence t h i s a t t a ck i s c a l l ed a p a s s iv e a t t a ck [ 4 ] [ 8 ] .

1 .1 .1 Mobile Ad -hoc Netw orks (MANET)

A d - Ho c ne tw o rk s h av e n o in f r as t r u c tu r e wh e r e t he no des a r e f r e e t o

j o i n an d l e f t t h e n e tw o rk . Th e no d es a r e co nn ec t ed wi th each o th er

t h ro u gh a w i r e l e s s l i nk . A no d e can s e r v e as a r ou t e r t o fo r w a rd th e

d a t a t o t h e ne i ghbo r no d es . A s a r e su l t , t h i s k in d o f ne t wo r k i s a l so

k n ow n a s i n f r as t r uc t u r e as f ew er n e tw o r ks . Th es e n e t wo r ks hav e no

cen t r a l i z ed ad min i s t ra t i o n . Ad - H oc ne t wo r ks h av e th e cap ab i l i t i e s t o

h and l e an y m a l fun c t io n i n g in t h e n o des o r an y ch an ges th a t t h e y

ex p e r i en ce d ue t o t op o l o g y ch an ges . Wh en ev e r a n od e in t h e n e t wo rk

i s do wn o r l e av es t h e n e tw o rk th a t c au s es t he l i n k b e t ween o th e r no d es

i s b r ok en . Th e a f fec t ed n od es i n t he n e t wo rk , s im pl y r eq u es t f o r new

r o u t es an d n ew l ink s a r e e s t ab l i s h ed .

Figure 1.1 Ad Hoc Networks [28]

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1 .1 .2 Chal lenge in MANETS

M A NE Ts a r e v e r y f l ex ib l e , i . e . n odes can f r ee l y j o i n an d l e av e t h e

n e tw o rk . T he r e i s n o cen t r a l i z ed bo d y t h a t keeps wa t ch in g o n the

n o des en t e r in g an d l e av in g t h e n e t w or k [ 28 ] . A l l t h es e w eak ness e s o f

M A NE Ts m ak e i t vu ln e r ab l e t o a t t a cks an d th es e a re

i . N o n S ecur e Bou nd ar i es

i i . C om pr omi s ed N od e

i i i . P ro b l em o f S ca l ab i l i t y

i) Non Secure Boundaries

M A NE T i s v u l n erab l e t o d i v e r s e k in d s o f a t t a cks d ue to n o c l ea r

s ecu re bo un d ar y. T h e n a tu r e o f M A NET , n od es h as t h e f re ed om t o jo in

an d l e av e i ns i d e the n e t w or k . A n od e can j o i n a n e t wo rk au tom a t i ca l l y

i f t h e n e t wo r k i s i n t h e r ad io r an ge o f t h e no d e , t hu s i t c an

c o mmu ni ca t e w i t h o t h er n od es in t h e n e tw o rk . Du e t o no s ecu re

b o un da r i e s , M AN ET i s mo r e d i s po s ed to a t t a ck s . Th e a t t a cks m ay b e

p a ss iv e o r a c t iv e , l e akage o f i n fo rm at io n , f a l s e m es sage r ep l y, d en i a l

o f s e r v i ce o r ch ang i n g t he d a t a i n t egr i t y . T h e l i n ks a r e c o mp ro mis ed

an d a r e op en t o va r io us l i nk a t t a ck s . A t t ack s on th e l i nk in t e r f e re

b e tw een th e no d es an d t h en i nv ad i n g th e l i n k , d es t r o yi n g t h e l i nk a f t e r

p e r f o r min g m a l i c i ou s b eh av io r . T h e re i s no p ro t ec t io n aga i n s t a t t a cks

l i k e f i r ew al l s o r acce s s co n t ro l , w h ich r e su l t i n t h e vu ln e r ab i l i t y o f

M A NE T t o a t t a cks . S po o f i n g o f no d e ’s i d en t i t y , d a t a t a mp er i n g ,

co n f id en t i a l i n f o rm at io n l e ak age an d i mp e rs on a t in g n o d e a r e t he

r e s u l t s o f s u ch a t t ack s w hen s ecu r i t y i s co mp ro mis ed [ 22 ] .

ii) Compromised Node

S om e o f t he a t t ac ks a r e t o ge t acce ss i n s i d e th e n e t wo rk i n o rd e r t o ge t

co n t ro l ov e r t h e no d e in t h e n e t w or k u s in g u n f a i r means t o c a r r y o u t

t h e i r m al i c io us ac t i v i t i e s . M obi l e n odes in M AN ET a r e f r e e t o mo v e ,

j o i n o r l e av e t h e n e tw o rk i n o th e r w o rd s th e mo b i l e no d es a re

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a u to nom ou s [ 2 3 ] . D u e t o t h i s au to nom ou s f ac t o r f o r mob i l e n od es , i t i s

v e r y d i f f i cu l t f o r t h e n od es t o p rev en t m al i c i ou s ac t i v i t y i t i s

co mmu ni ca t in g w i th . Ad - ho c n e t wo rk m ob i l i t y m ak es i t e a s i e r f o r a

co mp ro mis ed n od e t o ch an ge i t s po s i t i o n s o f r eq u en t l y m ak in g i t m ore

d i f f i cu l t and t ro ub l e som e t o t r a ck the m al i c i ou s ac t iv i ty . I t c an b e

s een t ha t t h e s e th r ea t s f r om co mp r omis ed n od es in s i d e the n e tw o rk a r e

m o re d an ge r ou s t h an a t t a ck i n g th r ea t s f r om o u t s id e t he n e t w or k .

iii) Problem of Scalability

In t r ad i t i o na l n e t wo r ks , w h e re th e n e t w or k i s bu i l t an d each m ach in e

i s co nn ec t ed to t h e o th e r m ach in e wi th th e h e lp o f a wi re . Th e n e t wo rk

t op o l o g y an d th e sca l e o f t h e ne tw o rk , wh i l e d e s i gn i n g i t i s d e f in ed

an d i t do e s no t ch an ge m uch d u r in g i t s l i f e . In o th e r wo rd s , w e can s a y

t h a t t h e s ca l ab i l i t y o f t h e ne tw o rk i s d e f i n ed i n t h e b eg in n i n g ph as e o f

t h e d es i gn in g o f t h e n e t wo rk . T h e ca s e i s qu i t e o pp os i t e i n M AN ET s

b ecaus e th e no d es a r e m ob i l e and due t o t h e i r mo b i l i t y i n M AN E Ts ,

t h e sca l e o f t h e M A NE Ts i s ch an gi n g . I t i s t oo h a rd t o kn ow and

p r ed i c t t h e nu mb ers o f no d es i n t h e M A NE Ts i n t he fu tu r e . T he no des

a r e f r e e t o mo v e in an d ou t o f t h e Ad - H oc n e t w or k , w h i ch m ak es th e

A d - Ho c n e t w or k v e r y m u ch s ca l ab le and s h r in k ab le . K eep in g th i s

p r op e r t y o f t h e MA N E T, t he p r o t o co l s an d a l l t h e s e r v i ce s t h a t a

M A NE T p ro v i d es m us t be ad ap t ab l e t o s u ch ch an ges .

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Figure 1.2 Challenges in MANET [28]

1 .1 .3 Ty pes of At tack in MANET Based On Per formance

A t t acks a r e c l as s i f i ed i n t o tw o g r o ups acco rd in g t o p e r f o rm an ce and

t h e n a tu r e o f t h e a t t a ck : P a ss i v e a t t a ck an d A ct iv e a t t a ck .

i. Passive Attacks

T h e a im o f t h i s a t t a ck i s t o op e r a t e s i l en t l y an d s t ea l s i gn i f i c an t

i n fo rm at io n f r om th e t a r ge t ed n e tw o rk . Usu a l l y, t h e a t t a ck e r d o es no t

d i s t u rb t h e n o rm a l n e t w or k ac t iv i t i e s s uch a s d ro pp in g p ack e t s [ 2 5 ] .

A cco rd in g l y, t h e a t t a cke r b ecom es p a r t o f t h e n e t wo rk and l i s t ens an d

m on i to r s t h e n e t wo r k t r a f f i c , wh i ch v io l a t es m es s age co n f i den t i a l i t y .

D e t ec t i n g t h i s k i nd o f a t t a ck i s v e r y ch a l l en g i n g as t h e ac t i v i t i e s and

o p e r a t i on s o f t he n e t wo r k a r e un af f ec t ed and n o new t r a f f i c i s

i n t ro du ced .

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ii. Active Attack

T h e a t t a ck e r , an un au t ho r i z ed p ar t y, d i s t u rb s n e t wo r k op e r a t io ns and

m od i f i es o r f ab r i ca t es m ess ages . The a t t a ck e r d i s t u r bs t h e no rm al

a c t i v i t i e s o f t h e n e t w or k . In ad d i t i o n , t h e i n t ru d e r can in s e r t , mo d i f y,

d e l e t e , r ep l y, o r d r o p p ack e t s u s i n g th i s a t t a ck . Al th ou gh i t i s pos s i b l e

t o d e t ec t t h es e a t t a cks qu i ck l y co m p a r ed t o a p as s ive a t t a ck , t h ey

can no t be p r ev en t ed [ 2 4 ] .

1 .1 .4 Je l ly f i sh At tack

T h e J e l l yf i s h a t t a ck i s o n e t yp e o f D en i a l o f S e rv i ce ( DO S ) a t t a ck t h a t

u su a l l y o ccu r s a t t h e t r an sp or t l a ye r o f t h e M AN E T s t ack . D ur in g t h i s

a t t a ck , a m al i c io us n o d e can r em ain ac t i v e i n p ack e t f o r w a r d i n g and

ev en r ou t e , d i s cove r in g t o i n h i b i t i t f r o m d i agno s i s an d d e t ec t i on .

H o w ev e r , t h e ma l i c i ou s n od e ma y a f f ec t t h e t r a f f i c b y i t s e l f v i a

d r op p i n g p ack e t s p e r io d i ca l l y , r eo r d e r i n g p ack e t s , o r o t h e r su ch

j i t t e r s . T hu s , J e l l yf i sh a t t a cks a r e cons id e r ed ha r mf u l t o T CP t r a f f i c as

co op e r a t iv e n od es can r a r e l y d i f f e r en t i a t e t h e a t t a ck f r om t h e n o rmal

n e tw o rk co n ges t ion . T he J e l l yf i s h a t t a ck i s c l a s s i f i ed a s ( J F -R eor d e r

A t t ack , J F - De l ay V a r i an ce At t ack an d J F Pe r i o d i c D ro p At t ack ) t he

m ai n o b j ec t i v e o f j e l l yf i s h a t t a ck i s t o r ed u ce th e th r ou gh p u t o f a l l t he

f l ow s b y e i th e r r e - o r d er in g t h e packe t s , i n c r eas i n g t h e en d to end

d e l ay o f t h e d a t a pack e t s , d r op p i n g a s m al l f r a c t io n o f pack e t s o r d rop

a l l t he d a t a p acke t s i t r e ce iv es . J e l l yf i s h a t t a cks ge t ex p lo i t ed

m al i c io us l y i n l au n ch in g lo w - r a t e T CP t a r ge t ed d en ia l o f s e rv i ce

a t t a ck ( D OS ) . A l s o a t yp e o f p a s s i v e a t t a ck b ecaus e i t do e s no t v i o l a t e

t h e ru l es o f r ou t in g and p ack e t f o r w a rd in g p ro t o co l s d i r ec t l y .

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T ransp o rt L ay er

A t r ans po r t - l a ye r p r o to co l p ro v id e s f o r l o g i ca l comm un i ca t i on b e tw een

ap p l i c a t io n p ro ces se s ru nn i n g o n d i f f e r en t h os t s . B y l o g ica l

co mmu ni ca t io n , w e m ean th a t f rom an ap p l i c a t io n ’s p e r s pec t i v e , i t i s

a s i f t h e h os t s r un n i n g t he p r o cess e s we r e d i r ec t l y co nn ec t ed ; i n

r e a l i t y , t h e ho s t s ma y b e o n op po s i t e s i d es o f t h e p l an e t , co nn ec t ed v i a

an y l i n k t yp es .

i . J e l l y f i sh R eo rd er A t t a ck

In J F -R eo r d er a t t ack , t h e m a l i c io us n o de d o es no t p u rs u e t h e b a s i c

f u n c t i on o f t h e F IFO I / P qu eu e fo r d a t a fo r wa r d i n g , an d i t r an dom l y

s e l ec t s t h e p ack e t s b e f o r e f o r w a rd in g t h em t o i t s su cce ss o r , a s sh own

i n F i gu r e 2 .3 . C umu l a t i v e s eq u en ce nu mb ers a r e us ed in T CP p r o t oco l s

t o i d en t i f y e ach byt e o f t h e p a yl o ad . Up on th e rece i p t o f an o u t - o f -

o r d e r m ess age b y t h e r ece i v e r , i t a ck n ow led ges th e s en d e r ab ou t t he

l a s t m ess age r ece i ved i n t h e co r rec t o rd e r . Th i s f o r ces t he v i c t im n od e

( i . e . So u rce no de) t o r e t r an smi t t h e m ess age wh ich i s n o t - ye t -

ack no wl ed ged . D ue t o p e r s i s t en t r eo r de r i n g o f p ack e t s b y an

i n t e rm ed i a t e no d e , t h e s end e r wi l l en t e r i n to a s low s t a r t s t a t e ,

t h ro u gh r e t r ansm iss io n o f t h e s egm en t , ov e r an d o v er aga i n , f o r t h e

n o t - ye t - a ckn o wl edged s egm en t sh ow ed th a t n e t w o rk p e r fo rm an ce

b ecom es wo rs e i n t h e p r e sen ce o f J F -R eor d e r a t t a ck [ 14] .

Figure 1.3 Jellyfish Reorder Attack [14]

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ii. JF-Delay Variance Attack

In J F - D e l ay v a r i ance a t t a ck , t h e m a l i c i ou s no de p r es e rv e s t h e b a s i c

o p e r a t i on o f t he F IFO I / P qu eu e w hi l e f o r w a rd i n g th e d a t a p ack e t s , bu t

i t d e l ays t h e p ack e t s f o r a r and om t im e b e fo r e f o rw a r d in g th em t o i t s

s u ccess o r as s ho w n i n F i g u r e 2 .4 In t h i s a t t a ck , m al i c io us no d es de l ay

t h e p ack e t s f o r a r an do m t i m e t o s end t he d a t a t r a f f i c i n b u rs t s l a t e r

[ 1 4 ] . Th i s s cen ar io u l t i m at e l y r e s u l t s i n m or e co l l i s i on s an d l os se s i n

t h e n e t w or k . F in a l l y , t h i s a t t a ck caus e s v e r y h i gh R TO b ecau s e o f

m ul t ip l e p ack e t l o s s e s . TCP has ve r y f i n e m ech an i sm s to h an d l e

n e tw o rk co n ges t i on , bu t t h e r e i s no wa y t o d e t e rm in e whe t h er t h e lo s t

p ack e t s a r e du e t o n e tw o rk con ges t io n o r J F - At t ack . H ence , i t i s v e r y

d i f f i cu l t t o d e t ec t an d mi t i ga t e t he d i f fe r en t v a r i an t s o f J F - A t t ack s .

Figure 1.4 Jellyfish Delay Variance Attack [14]

iii. JF-Periodic Drop Attack

In J F - Pe r io d i c D ro p a t t a ck , t he mal i c io us n od e r an do ml y d i sca r ds

e i t h e r a f r a c t i on o f p acke t s o r d i sca r d s a l l t h e p ack e t s f o r a sm al l

f r a c t io n o f t i m e dur i n g t h e on - go in g co mmu ni ca t io n p roce s s a s sh o wn

i n F i gu r e 2 . 5 . Th e t im e p a t t e r n i s d ec i d ed b y t h e a t t ack er . Th i s a t t a ck

ex p l o i t s t h e w eak nes s o f TCP , wh ich m eans th a t i f an ack n ow led gm ent

( A CK ) fo r an ou t s t and i n g s egm en t ha s no t b een rece ived b ef o r e t h e

ex p i r a t i on o f R e t ran smi ss io n T im eou t ( RT O ) v a l ue , t hen t h e s end e r

t ak es t h i s t im e ou t a s an in d i ca t i on o f s ev e re co n ges t io n an d en t e r s t h e

s lo w s t a r t p has e . E v e r y t i m e th e R T O v a l ue i s d o ub l ed wi t h

r e t r an smi ss i on o f s egm en t s ( no t - ye t - ack no wl ed ged) u n t i l r e ach i n g a

t h re sh o l d RT O v a lu e , an d th e r ea f t e r t h e TCP co nn ec t io n i s t e rm in a t ed

[ 1 4] . F i n a l l y , t he en d - t o - end t h ro u ghpu t i n t h e p re s en ce o f J F -P e r i od ic

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a t t a ck o f t h e n e t wor k d egr ad es v e r y b ad l y.

Figure 1.5 Jellyfish Periodic Drop Attack [14]

1 .2 Problem Statement

A m on g m an y co n ce r n s i n m ob i l e ad - ho c n e t wo r ks , s ecu r i t y i s a

p r omi n en t on e . So f a r , d i f f e r en t s tud i es h av e b een con d uc t ed t o f i l l

t h i s s ecu r i t y h o l e i n su ch n e tw o rk s . Fo r ex am pl e , i n mo b i l e ad - ho c

n e tw o rk s , v a r io us a t t a cks h av e b een d e t ec t ed us i n g d i r ec t t r us t - b as ed

d e t ec t i on and i t i s o n e co mmon s o lu t io n t o i d en t i f y an d

co un t e r m easu r e t he J e l l yf i s h - a t t a ck er s i n sm al l a s w e l l a s l a r ge

M A NE T s cen a r io s [ 1 2 ] . H ow ev er , i n t h i s d e t ec t i on m echan i sm , a l o t o f

i nn o cen t n od es a r e d e t ec t ed as m a l i c i ou s n od es b ecau s e o f

i n ap pr o pr i a t e o v erh ea r i n g o f d a t a pack e t s d u r in g t h e p r omi s cu ous

m od e , du e t o i n t e r f e r en ces , r ad io t r ans mis s i on e r ro r s , n e t w o rk

co n ges t i on o r p ack e t co l l i s i on s an d n od e m ob i l i t y . T o in c r eas e th e

accu r acy o f t h i s d e t ec t i on m ech an i s m to an o th e r app r o ach ca l l ed

i nd i r ec t m on i to r i n g m e th od s w as p ro po s ed [ 11 ] . In t h i s m et ho d , a l l t h e

n e i ghb o rs o f a n od e wi l l m on i to r an d s h a re t h e i r ob se r v a t io ns wi th

each o t he r . T h i s ap p ro ach d ec r eas es t h e fa l s e J e l l yf i s h p e r i od i c d r op

a t t a ck , b u t n o t accu r a t e an d app rop r i a t e . J e l l yf i s h Pe r io d i c Dr op

A t t ack can a l s o be d e t ec t ed b y a F r i en ds h i p Bas ed J e l l yf i s h A t t ack

D e t ec t i on Al go r i t hm ( FJ A D A) [ 1 4] . I t i s p r es en t ed fo r M ob i l e A d H oc

N e t wo rk s , w h e re th e b as i c co n cep t o f f r i en ds h i p m ech an i s m i s ad ded

t o t h e ex i s t i n g D i rec t T ru s t - ba s ed D et ec t io n ( DT D ) a l gor i t hm to keep

t h e i mp or t an t r e s ou r ce s o f a n od e in o bs e rv in g t h e ac t i v i t i e s o f i t s

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o n e -h op n e i ghb o rs , t h ro u gh p ro mis cuou s m od e . In t h i s mech an i s m, t he

d e t ec t i on i s mo r e r o bu s t t h an t h e DT D . Bu t t h e ma l i c i ou s n od e an d

b en i gn n od e t h r es ho ld va lu e a r e equ a l t o 10 , 1 0 , r es pec t iv e l y t h e v a l ue

i s ha r d co d ed . To se t t h e t h r e sh o ld v a l u e s t a t i c , w e d o no t kn ow h ow

m an y p ack e t s a r e d r op p ed b y t h e ma l i c io us no d es to d ec id e i t i s a

m al i c io us no d e . So , we n eed t o s e t t h e b en i gn and m al i c io us no d e

t h re sh o l d v a lu e dyn am i ca l l y t o i n c r ea s e th e accur acy o f J e l l yf i s h

p e r i od i c d ro p a t t a ck d e t ec t i on r a t e . H en ce , t h i s r e s ea r ch wo rk

a t t empt s t o ans w er t h e fo l l ow in g r es ea r ch q u es t io ns :

Wh at a r e t h e p e r fo r m an ce m et r i c s us ed t o ev a l u a t e t h e de t ec t io n

m echan i sm w i th re s p ec t t o t h e J e l lyf i s h p e r io d i c d rop a t t ack

u n de r t he AO D V p ro to co l?

H o w to s e t t h e m in im um th r es ho ld va l u e t o com pa r e wi th t h e

D r o p co un t v a l u e th a t c an in c r eas e t he accu r acy l ev e l o f M T V-

J PD A DA?

H o w to d es i gn an a l go r i thm th a t c an i n c r ea s e t h e accu r ac y l ev e l

o f J e l l yf i s h p e r i od ic d ro p a t t ack d e t ec t io n r a t e?

1 .3 Research Object ives

1 .3 .1 Genera l O bjec t ive

T h e gen e r a l o b j ec t i v e o f t h i s s tu d y i s t o an a l yz e t he i mp ac t s o f a

J e l l yf i s h p e r i od ic d r o p a t t ack on t h e pe r f o r m an ce o f t he A O D V

p r o t oco l on M A NET an d t h en d es i gn an a l go r i t hm th a t c an en han ce

d e t ec t i on o f J e l l yf i s h p e r io d i c d ro p a t t a cks w h en com p ared aga i ns t t h e

ex i s t i n g wo r k .

1 .3 .2 Speci f i c Objec t ives

T h e sp ec i f i c o b j ec t i v es o f t h i s s t ud y a r e :

T o id en t i f y p e r f o r m an ce m et r i c s us ed f o r ev a l u a t i on o f t he

A O D V r ou t in g p ro to co l w i th aga ins t t h e p r op os ed ap p ro ac h .

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T o i mpl emen t t h e J e l l yf i s h p e r io d i c d r op a t t ack i n t h e A O DV

r o u t i n g p r o t oco l .

T o d ev e lo p an a l go r i th m th a t c an enh an ce d e t ec t i on o f J e l l yf i s h

p e r i od i c d r op .

T o imp l em en t t he p r o pos ed m in i mu m - th r e sh o ld v a l ue b a s ed

J e l l yf i s h p e r i od i c d r o p a t t a ck d e t ec t ion un de r A O D V a l go r i th m.

T o ev a lu a t e t h e p e r f o rm ance im p ac t o f t h e p ro po sed a lgo r i t hm

w i t h t h e ex i s t i n g o n e , wi th r es p ec t t o t h e J e l l yf i s h pe r iod i c d r op

a t t a ck .

1 .4 Scope and Limitat ion

T hi s s tu d y h a s i m pl em en t ed a mi n i mum th r es ho ld v a l u e b a s ed J e l l yf i sh

p e r i od i c d r op a t t a ck an d i t s d e t ec t io n a l go r i thm ( M TV -J PD A D A ) .

T h e s t ud y h a s t h e fo l l ow in g l imi t a t i on :

Becau s e o f t im e co ns t ra in t , t h i s s t ud y d i d n o t co ns id er a l l J e l l yf i sh

a t t a ck v ar i an t s ex cep t J e l l yf i s h p e r i od i c d r op a t t a ck and a l so d i d no t

co mp a r e to o t h e r wo r ks .

1 .5 Methodology

W e us e th e fo l lo win g m eth od o l o g y t o p u t fo r w ar d th e p rop os ed

ap p ro ach an d th es e a r e :

1 .5 .1 Literature Review and Re lated Works

In t h i s t h es i s wo r k , a n umb er o f p ub l i sh ed re s ea r ch p ape r s , com pl e t e

r e s ea r ch wo r ks , bo o ks an d w eb s i t e s i n t h e a r ea o f M A NE Ts w e re

o bs e r v ed .

1 .5 .2 Tools and S imulator

Ex plo r i n g t h e r equ i red to o l s an d t e ch no lo g y w i th t he h e l p i n t he

D e t ec t i on o f M ob i l e Ad H o c N et w or ks At t ack , t h e t o o l s and

t e chn o lo g y w e h av e u s ed i n t h e r es ea r ch w e r e p re s en ted i n Ch ap t e r 4

o f t h i s d o cu ment a t io n .

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1 .5 .3 Prototyp ing

T he p r op os ed app ro ach d emo ns t r a t e d i n t h i s t h es i s w o rk , w e u sed a

m od e l as a m eans o f ex p r es s t h e con cep t i on .

1 .6 The Signif icance of the Study

T h e s t ud y h a s t h e fo l l ow in g s i gn i f i c ance

W e d ev e l op ed a b e t t e r a l go r i th m t h a t i n c r eas e s t h e d e t ec t i on r a t e

o f t he J e l l yf i s h p e r i od ic d r op a t t a ck .

W e a l so r ecomm en d ed a d e f en s e m echan i sm in th e A O D V

M A NE T r ou t i n g p ro to co l w i th r es pec t t o t h e J e l l yf i s h p e r i od i c

d r op a t t a ck .

I t w i l l b e u sed a s a r e f e r en ce f o r fu tu re r e sea r ch wo r k .

1 .7 Thesis Organizat ion

T h e r em a in i n g pa r t o f t h i s t h e s i s i s o r gan iz ed a s fo l l ow s . C h ap te r 2

d ea l s wi th t h e l i t e r a tu r e r ev i ew and d e s c r i b e s t h e - s t a t e - o f - t he - a r t i n

r e l a t i on t o MA N ET a t t a ck sp ec i f i c a l l y J e l l yf i s h A t t ack . Ch ap t e r 3

P r es en t ou r M in i mu m -T hr e sh o l d V a l ue Bas ed J e l l yf i s h P e r i od i c Drop

A t t ack D e tec t io n A l go r i t hm (M T V -JP D AD A ) t h a t i s h i gh l y r e l ev an t

an d m or e r e l a t ed to imp l em en t a t i on i s su e s o f t he J e l l yf i sh a t t a ck and

i t s d e t ec t i on a l go r i t hm . C hap t e r 4 p r es en t s im pl em en t a t io n r es u l t an d

d i s cuss io n p a r t F i na l l y , C h ap t e r 5 p re s en t s t h e su mm ary , c o n c l us ion ,

an d f u t u r e w o rk .

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Chapter 2 Related Works

2 .1 Related Works

Fr i end sh i p Bas ed J e l l yf i s h At t ack De t ec t io n Al go r i thm ( FJ AD A ) i s

p r e s en t ed f o r M obi l e Ad H o c N et wor k s wh e r e th e b a s i c co ncep t o f

f r i en ds h i p m ech an i s m i s ap p en de d t o t h e ex i s t i n g D i r ec t T ru s t -b a s ed

D e t ec t i on ( DT D ) a l go r i thm i n o r de r t o k eep t he ene r g y r e s ou r ces o f a

n o de b y n o t o b se rv in g t h e ac t iv i t i e s o f i t s f r i en d n od es [ 1 4 ] . FJ AD A

r ed u ce s th e p os s ib i l i t y o f b l ack l i s t i n g th e i nn o cen t n od es b y g i v i n g a

s econ d o pp or tu n i t y t o t h e s us p ec t ed no d es a f t e r b l o ck in g t he i r s e r v i ces

f o r a f i x ed du r a t i on o f t im e . Th e p e r f o rm an ce o f t h e p r op os ed

a l go r i thm i s ev a lu a t ed i n t e rms o f t h e p ack e t d e l i ve r y r a t i o , t he

av e r age en d - to - en d d e l ay, n e t w o rk th r o u ghp u t , t h e d e t ec t i on r a t e an d

f a l s e p os i t i v e r a t e w i t h i n c r eas i n g t h e J F - D el ay V a r i an ce , J F - Reo rd er

an d J F -P er io d i c Dr o p a t t ack e r no des i n t h e n e t w or k . Th e s i mu la t i on

r e s u l t s , ev i d en t l y s ho w th a t t h e p ro po s ed a l go r i t hm i s v i go ro us , and

a l so sh o w i t s e f fec t i v en ess and d e t ec t io n e f f i c i en c y i n t e r ms o f

d e t ec t i on ra t e and f a l s e p os i t i v e r a t e m et r i c s . Th e p r op os ed a l g o r i thm

h as q u i ck l y an d accu r a t e c ap ab i l i t y t o d e t ec t t h e J e l l yf i s h a t t a ck e r

n o des i n t h e n e t wor k . Fu r th e rm o r e , i t a l so r e s t r i c t s t h e ab i l i t y o f t h e

m al i c io us no d es t o c au se f u r th e r d amage t o t h e n e t wo r k . Bu t Ben i gn

an d M al i c i ou s no d e T hr e sh o l d va lu e i s s t a t i c .

H en ce S ecur i t y o f M A N ET i s o n e o f t h e imp o r t an t f ea t u r e s fo r i t s

d ep l o ym en t . In t h i s t h es i s , t h ey h av e an a l yz ed t h e b eh av io r and

ch a l l en ges o f s ecur i t y t h r ea t s i n MA N E T wi t h so lu t io ns . A l th ou gh

m an y s o l u t i on s h av e b een p r op os ed s t i l l t h os e a r e n o t i mm acu l a t e as

f a r a s v i ab i l i t y an d p r o f i c i en c y . O n th e o f f ch ance t ha t an y

a r r an gement f un c t io ns adm i r ab l y w i t h i n t h e s i gh t o f a s in g l e m al i c i ous

n o de , i t m ay n o t b e r e l ev an t i f t h e re s ho u l d a r i s e an o ccu r r en ce o f

d i f f e r en t ma l i c i ous n od es? To w r ap th in gs u p t h ey o v e r f l o wed th e

b u nd l e t o a d i f fe r en t no d e an d edu ca ted t hem abo u t J e l lyf i s h A t t ack i s

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h app en i n g p r em is e a t t h e t o p o f h igh en d to end de l a y an d J i t t e r

p a r am e te r s , so t h a t t h e en t i r e n od e b reak s t he cu r ren t p a t h an d f in d t h e

a l t e r n a t e r ou t e f o r d a t a t r ans mis s io n . U s in g t h i s m e tho d t h ey m a y

r ed u ce t h e e f f ec t o f a J e l l yf i s h a t t a ck .

S ecu r i t y co m es f rom a t t a ck s . J e l l yf i s h a t t a ck i s d e l aye d d a t a p ack e t s

f o r so me amo un t o f t im e , w h i ch r esu l t s i n h i gh en d - to - end d e l a y i n t h e

n e tw o rk . T h e P r opo s ed app ro ach d e t ec t an d p r even t a J e l l yf i s h a t t a ck

b y co n s id e r i n g s en d i n g t im e and rece iv in g t i m e o f t h e p ack e t ,

t h re sh o l d t i me o f t h e p ack e t and t h e l o ad o f t h e ne tw o rk . Us i n g th i s

ap p ro ach th e y d e r iv e th a t d e l ay o ccu r s du e t o co n ges t io n o r J e l l yf i s h

n o de . Th i s w ay d e t ec t s an d p r ev en t s J e l l yf i s h a t t a ck an d i mp r ov es th e

p e r f o r man ce o f t h e n e tw o rk b y r ed u c in g t h e co n ges t i on an d J e l l yf i s h

n o de [ 13] . Bu t t h e pr op os ed s ys t em co n s id e r s o n l y J e l l yf i s h d e l ay

A t t ack .

IO T i s , b as i ca l l y i t i s v a lu e - ad d ed se r v i ce s w h i ch co nn ec t d i f fe r en t

d ev i ces w i th d i f fe r en t p l aces and w i t h d i f f e r en t p u rp os e s . W hi l e

co nn ec t in g t o t h e in t e r n e t i t i s h i gh l y v u ln e r ab l e t o v a r io us k in ds o f

a t t a cks . O n e i s a Syb i l a t t a ck an d an o t h er i s a J e l l yf i s h a t t a ck . I f an y

o f t h e a t t a cks in t he n e tw o rk , t hen t h e p e r f o r m an ce wi l l b e d ec l i n ed to

l o w. T o p ro t ec t t he n e t wo r k f ro m such s i t u a t io ns , t rus t v a l u e b as ed

t e chn i qu e i s u s ed . Wh er e each n od e m ark s t h e t r us t v a lu e o f h i s n ex t

n e i ghb o r . I f t h e n e i gh bo r no d e fo r wa r d s t h e pack e t s , t h en th e t ru s t

v a lu e wi l l b e ma r ked a s i n c r em en t ed e l se w i l l b e d ec r em en t ed o f t he

t r us t v a lu e d r ops b e yo n d t h e th r es ho ld v a lu e , t h en t he n od e w i l l b e

m a rk ed as a m a l i c i ou s n od e i s ma r k ed a s a t ru s t ed n od e . T h e

d i f f e r en ces be tw een S yb i l an d J e l l yf i s h At t a ck a f t e r d e t ec t i on

p e r f o r man ce an a l ys i s r es u l t s . I t g i v e s rem ar k ab l e d i f f e ren ce and

e f f i c i en t r es u l t s a f t e r d e t ec t an d r emo v e th e m al i c i ou s n o des and d a t a

t r an s f e r en d to en d co mmu ni ca t io n .

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T h e pe r f o r m an ce o f t h e n e t w or k u nd er a d i f f e r en t n um ber o f a t t ack e rs

h a s b een t es t ed . In a l l t h e c as es t h e p e r f o r man ce p a r ame t e r s l i k e t h e

en d t o end d e l ay a n d t h r ou gh p u t h a ve b een enh an ced . T h us , t h e t r us t

v a lu e b as ed t e chn i qu e w i l l b e u se fu l i n a l l s i t u a t i ons . IO T u n d e r

d i f f e r en t t yp es o f a t t a cks i s b e i n g h an d l ed u s i n g t ru s t -ba s ed s ch em es .

In a l l t h e scen a r io s t h e pe r f o r m an ce i s up gr ad ed . In f u tu r e va r io us

o th e r t yp es o f a t t a ck s can a l so be t e s t ed wi t h t he s am e t r us t - b as ed

s ch em e [ 27 ] .

I t h a s b een con c lu d ed th a t du e t o t h e d ecen t r a l i z ed n a tu r e o f t h e

m ob i l e Ad - Ho c n e t w or k , m al i c i ou s n o des en t e r t h e ne t wo r k w hi ch

t r i gge r s v a r i ou s typ es o f a c t iv e and p a ss i v e a t t acks . S ecu r e and

e f f i c i en t r ou t in g t ech n i qu es h av e b een w o rk ed o n t h i s p ap e r . In f u t u re

t e chn i qu e wi l l b e p r o po s ed wh i ch d e t ec t ed and i s o l a t e m al i c io us no des

f r om t h e ne tw o rk [ 1 ] .

T h e a t t a ck in wi r e l e s s n e t wo r ks wh ich i s v e r y d i f f i cu l t t o d e t ec t a s i t

f o l lo w s a l l t he r u l e s o f T r an smi ss ion C on t r o l P r o t oco l ( TCP ) . Th e

s t ro n g n ov e l m ech an i s m i s t h e n eed o f t h e h ou r t o d eve lop i n o rd e r t o

o v e r com e th i s a t t a ck i n t h e n e t w or k . Th e y u s ed a G en e t i c A l go r i thm a s

a t ech n iq u e to comb a t t h e a t t a ck an d o p t imiz e th e n e t w or k an d p ro v id e

a d e fens e fo r Mo bi l e A d Ho c N e tw o rk s aga i ns t t h i s t e ch n iq u e [ 1 ] .

M os t o f t h e ex i s t i n g p ro to co l s an d so lu t io ns a re a t t a ck - o r i en t ed t h a t ,

a r e t h e y f o cus in g o n p a r t i cu l a r a t t a ck and n eg l ec t o the r a t t a ck s o r

co l l ap s e in t h e p r es en ce o f u n i d en t i f i ed and un an t i c i p a t ed a t t a ck s . Th e

s ecu r i t y s o lu t io n m us t en com p as s a w i de r p e r sp ec t i v e i nv o l v in g b o th

k n ow n and u nk now n a t t a ck s . So dev e lo p in g m ul t i - f en ce s e cu r i t y

s o l u t i on i s an a r ea o f f u t u r e r e sea rch . Th e r e i s a t r ad e - o f f b e t w een

s ecu r i t y an d n e tw or k p e r fo r man ce . The n eed o f t h e ho u r i s t o i n t eg r a t e

s ecu r i t y w i th QoS ( Q u a l i t y - o f - S e rv i ce ) so t h a t o p t i miz ed s ecu r i t y

s o l u t i on s a r e d ev e lo p ed fo r M AN E T [ 3 ] .

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I f go o d t i m e s e r v i ce s an d no l os s o f i n f o rm at i on needs , t h en th e y h ave

ch os en T OR A and i f t h e y w an t a l ow d e l ay p r o d u ced du r i n g

t r an smi ss io n and recep t io n o f i n f o rma t i on and da t a t h en th e y go f o r

A O D V. G RP i s u s ed a s op t io n a l i n t h e p l ace o f A O DV . As com p ared to

t h e o th e r t h r ee p ro to co l s t h e p e r f o rm an ce o f DSR i s p o or . I f t h e y

i n c r ea s e no d e d en s i t y , t h e fo r w ar d i n g r a t e o f p ack e t s , u s e a d i f f e r en t

p r o t oco l an d in t ro d uced J e l l yf i s h p e r i od i c d r op p in g a t t a ck t he

p e r f o r man ce m a y v a r y. T h i s wo r k can b e f u r t h e r ex t end ed t o c a l cu la t e

t h e p e r f o r m an ce o f M ob i l e ad -h oc ne tw o r ks [ 4 ] .

T h ey d i d a com p ar a t i v e an a l ys i s o f t h ree k in ds o f J e l lyf i s h At t acks

w i t h s e l f i s h b eh av i o r At t ack un d e r t h e AO D V r ou t in g p ro to co l and

p r e s en t ed th e i r f i nd in gs . T h ey d i d an a l ys i s wi th r es p ec t t o d i f f e r en t

n e tw o rk s i z e s and un de r t h e p r e sen ce o f a d i f fe r en t nu mb er o f

a t t a ck er s i n t he ne tw o r k . T h ey d i d a l o t o f s im ul a t io n and an a l ys i s an d

a r r iv ed a t s i gn i f i can t and in t e rp r e t ab l e r e su l t s . T he y m eas u r ed t h e

i mp ac t o f t h e a t t a ck s wi th su i t ab l e m et r i c s an d ex p l a in ed t h e n a tu r e o f

d i f f e r en t a t t a ck s i n t h e i r wo r k . Wi th r esp ec t t o t he in c r eas e o f

m al i c io us no d es in t h e n e tw o rk , t h e p e r f o r man ce i s ge t t i n g d ec r eas ed

w i t h r es p ec t t o mo s t o f t h e me t r i cs t h a t t h e y co n s id er ed . Th e m ain

s cop e o f t h i s p ap er i s t o co mp a r e the Se l f i s h Beh av io r A t t ack w i th

d i f f e r en t J e l l yf i s h A t t acks . T he y s u cce s s fu l l y d i d th a t an d t h e r e su l t s

a r e mo r e i n t e re s t i ng . A cco rd i n g to t he i r o bs e rv a t io ns and th e y a r r i ved

r e s u l t s , t h e S e l f i sh Beh av i o r A t t ack i s mu ch w o rs e t h an a l l t yp es o f

J e l l yf i s h At t acks w i t h r e sp ec t t o mo s t o f t h e me t r i cs [ 8 ] . Bu t O n l y

P e r fo rm an ce eva lua t i on , d o es n o t i n c lu d e d e t ec t i on o r p r ev en t io n

m echan i sm.

M A NE T can b e dep lo yed ea s i l y i n a s i t u a t i on w h e re a t r ad i t i o na l

n e tw o rk i s no t pos s i b l e d ue t o i t s s p ec i a l ch a r ac t e r i s t i c s s uch as

f l ex ib i l i t y an d d yn ami c n a t u r e . T h e a i m b eh in d t h i s r e sea r ch pap e r i s

t o ana l yz e t h e e f fec t o f m an y a t t a cks u nd e r C BR t r a f f i c i n d i f f e r en t

s cen ar io s f o r DSR M A NE T r ou t in g p r o to co l . Based o n i nv es t i ga t i on s

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an d d a t a an a l ys i s o f s im ul a t i on r e su l t s , i t i s con c lu ded th a t wi th ou t

t h e p r es en ce o f any r o u t in g a t t a ck DSR p e r f o rm w el l i n l i gh t l y l o ad ed

n e tw o rk s . Bu t t h e p r e s en ce o f a b l ack h o l e , g r a y h o l e , an d ru sh in g

a t t a ck a t t h e t im e o f ro u t i n g e f f ec t s o n th e o v er a l l p e r fo r man ce o f t he

D SR p r o to co l b y d ec r eas in g th e p ack e t d e l i v e r y r a t i o and av e r age

t h ro u ghp u t bu t b y t h e i n c r ea s in g av er age en d to end d e l ay [ 9 ] .

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2 .2 Summary

Table 2.1 Related works Summary Y e a r T i t l e A i ms M e t h o d s C o n c l u s i o n D r a wb a c k s

2 0 1 6 D i r e c t

T r u s t -

b a s e d

D e t e c t i o n

A n d

R e c o v e r y

P r o c e s s Of

J e l l y f i s h

A t t a c k In

M AN E T

T h e p r o p o s e d wo r k

M o n i t o r , De t e c t ,

R e h a b i l i t a t e

( M r DR) t e c h n i q u e

i s c a r r i e d o u t .

N S 2 T h e p r o p o s e d

a p p r o a c h

d e c r e a s e s t h e

f a l s e J F -

a t t a c ke r

d e t e c t i o n s

c a u s e d b y t h e

i mp r o p e r

o v e r h e a r i n g o f

d a t a p a c ke t s a n d

d i s c a r d t h e

a t t a c ke r n o d e .

I t d e c r e a s e s

t h e f a l s e J F

a t t a c ke r

n o d e , b u t i t

d o e s n o t

s t o p J F

a t t a c ke r .

2 0 1 7 A n

E v a l u a t i o n

O n S e l f i s h

B e h a v i o r

A t t a c k

A n d

J e l l y f i s h

A t t a c k s

U n d e r

A O DV

R o u t i n g

P r o t o c o l

C o mp a r a t i ve

a n a l ys i s o f t h r e e

k i n d s o f J e l l y f i s h

A t t a c k s w i t h

S e l f i s h Be h a v i o r

A t t a c k u n d e r

A O DV r o u t i n g

p r o t o c o l .

N S 2 T h e S e l f i s h

B e h a v i o r A t t a c k

i s mu c h w o r s e

t h a n a l l t yp e s o f

J e l l y f i s h

A t t a c k s w i t h

r e s p e c t t o mo s t

o f t h e me t r i c s .

O n l y

P e r f o r ma n c e

e v a l u a t i o n

d o e s n o t

i n c l u d e

D e t e c t i o n o r

p r e ve n t i o n

me c h a n i s m.

2 0 1 7 J e l l y f i s h

A t t a c k

D e t e c t i o n

a n d

P r e ve n t i o n

i n M A N E T

T h e P r o p o s e d

a p p r o a c h d e t e c t s

a n d p r e ve n t s

j e l l y f i s h a t t a c k b y

c o n s i d e r i n g

s e n d i n g t i me a n d

r e c e i v i n g t i me o f

t h e p a c ke t .

N S 2 T h e p r o p o s e d

S y s t e m

I mp r o ve s

p e r f o r ma n c e o f

n e t w o r k b y

r e d u c i n g t h e

c o n ge s t i o n a n d

j e l l y f i s h

a t t a c ke r n o d e .

T h e p r o p o s e d

s y s t e m

c o n s i d e r s

o n l y

J e l l y f i s h

d e l a y A t t a c k .

2 0 1 8 F r i e n d s h i p

B a s e d

J e l l y f i s h

A t t a c k

D e t e c t i o n

A l go r i t h m

f o r M o b i l e

A d H o c

N e t wo r ks

In c r e a s i n g a t t a c k

d e t e c t i o n & s a ve

t h e va l u a b l e

r e s o u r c e s a n d

mi n i mi ze s t h e

p o s s i b i l i t y o f

o v e r e s t i ma t i n g t h e

ma l i c i o u s b e h a v i o r .

M AT L A B T h e p r o p o s e d

s y s t e m q u i c k l y

a n d a c c u r a t e

c a p a b i l i t y t o

d e t e c t t h e

J e l l y f i s h

a t t a c ke r n o d e i n

t h e n e t wo r k .

B e n i g n a n d

M a l i c i o u s

n o d e

T h r e s h o l d

v a l u e i s

s t a t i c .

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Chapter 3 Minimum Threshold Value Based Jellyfish

Periodic Drop Attack Detection Algorithm (MTV-

JPDADA)

W e h av e th e fo l lo wi n g s t age s t o i mpl em en t ou r M T V -J P DA D a l go r i t hm .

3 .1 Drop Count Calculat ion

D r o p co un t i s c a l cu l a t ed o n a p e r cen t v a l u e b y co u n t ing t h e d r op p ed

p ack e t s o f e ach no d e d iv id e b y t h e f o r w a rd ed p ack e t s o f e ach n od e

co un t and mu l t i p l y b y h u n dr ed .

100*)(

unttForwardCoTotalPacke

ountTotalDropCDCDropCount _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 1.3

3 .2 Minimum Threshold Value (MTV)

T h e min imu m t h r es ho ld v a l u e (M TV) i s i so l a t i n g a g iv en no d e i s a

m al i c io us o r i n nocen t . B y co m p ar ing t h e mi n i mum t h r e s ho l d v a lu e

w i t h th e d r op co un t . I t i s n o t r e commen d ed t ak in g a n a rb i t r a r i l y v a l ue

a s a t h r es ho l d v a lu e i n r e l a t ed w or k m ay c l a s s i f y n o r m al no de as a

m al i c io us n od e and v i ce - v e rs a . To av o i d th i s w e us e d a mi n im um

t h re sh o l d v a l u e . Th i s t h r es ho l d v a l u e i s ob t a in ed f r om th e s im ul a t ion

s cen ar io wh i ch i s co nd u c t ed to an Ad H oc n e t wo rk to po lo g y an d b y

t ak in g a m ax i mum p ack e t d ro p co un t i n a n o rm al A d H o c n e t w or k

s cen ar io , wi t ho u t a J e l l yf i s h p e r i od ic d r o p a t t a ck . Th e p ack e t d r op i s

o ccu r r in g in an y n o r ma l A d H o c n e t wo r k b y co n ges t io n , co l l i s io n , and

i n t e r fe r en ce as we cou ld s ee f r om th e S cen a r i os . T h e M TV i s

c a l cu l a t ed b y e x ami n i n g and m oni to r in g t h e d ro p p in g p ack e t f rom t he

n o rm al n e t wo r k and t ak in g th e m ax imu m p ack e t d r op coun t o ccur r ed in

t h e n o rm al a rb i t r a ry n e t w o r k wi t ho u t J e l l yf i s h p e r io d a t t a ck ) d i v i d ed

b y t o t a l t r ansm i t t ed p ack e t s an d mu l t i p l i ed b y 1 0 0 a s s ho wn i n

eq u a t i on 3 . 2 . W h er e , t h e m ax im um p ack e t d r op cou n t i n o u r n o rm al

u n i n fec t ed n e t wo r k s im ul a t io n i s 19 Pack e t s .

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G iv en : M ax imum Pack e t D ro pC ou n t = 1 9 .

100*

unttForwardCoTotalPacke

ntketDropCouMaximumPacMTV _ _ __ __ __ __ __ __ ___ _ __ __ __ __ _ 2.3

3 .3 Proposed Model

T h e P r op os ed A p p ro ach o f Min im um -T h r es ho l d Bas ed J e l l yf i s h

P e r i od i c D ro p At t ack D et ec t io n A l go r i t hm ( M TV -J PD A DA ) i s

d e s c r ib ed in t h i s s ec t io n . M T V -J PDA D A i s p r im a r i l y an ex t en ded

v e r s io n o f FJ A DA [ 1 2] , b y a s s embl ing u s e o f t h e con cep t o f f r i en ds h i p

i n ad d i t i on to t h e b a s i c fu nc t i on a l i t y o f t h e FJ A D A. A F r i en ds h ip

T ab l e i s m ai n t a i n ed b y ev e r y n o d e , co n t a i n i n g th e ID s o f n od es , wh i ch

a r e e i t h e r d i r ec t f r i en ds o f t h e n od e o r i nd i r ec t f r i en ds ( f r i en ds o f

d i rec t f r i end s ) o f t h e no d e . In ad d i t i on to t h e F r i en dsh ip T ab l e , ev er y

n o de a l s o m ai n t a i ns M al i c io us T ab le an d Beh av i o r M oni to r i n g T ab le

f o r i t s ne i ghb o rs . A P ack e t f o r w a rd e r no d e add s t o t h e Beh av io r

M on i t o r in g T ab l e i t s o n e - ho p n e i ghb or n od es . P acke t For w ar d er N od e

m ak e f r i end s a f t e r b ecomi n g aw ar e o f t h e i r goo d b ehav io r o v e r a

p e r i od o f t i m e . F r i en d no d es a r e t hose n o d es w h i ch a r e co ns id e r ed a s

t h e mo s t t ru s t ed n o des in t h e n e tw o r k and can b e co ns i d e r e d i n

f o r w a rd i n g th e pack e t s . O n t h e p ro pos ed a p p ro ach , e ach n o de sh a r es

t h e d e t a i l s ab o u t i t s f r i end n od es p re s en t i n t he f r i en ds h i p t ab l e and

m al i c io u s n od es p re s en t i n t h e m al i c io us t ab l e t o a ccu r a t e l y j u d ge t h e

b eh av io r o f n od es . T h i s con cep t o f sh a r i n g th e d e t a i l s o f f r i end no d es

an d ma l i c i ou s n od es amo n g t h e f r i en d n o d es w ou ld h e l p i n m in imiz i n g

t h e p os s ib i l i t y o f b l ack l i s t i n g th e inn o cen t n od es du e to t r ans mis s i on

e r r o r s , n e t w or k con ges t io n o r p ack e t co l l i s io ns on th e ad ho c n e t wo r k .

M T V -J PD AD A b lack l i s t s an d i s o l a t e s t ho s e mo b i l e n o des w h i ch

i n t en t i on a l l y p e r f o r m m a l i c i ou s ac t iv i t i e s f rom th e no rma l f un c t i o n in g

n e tw o rk . M T V -J PD A D A i s m o r e s t r on g an d r ed u ces t h e n ega t iv e

i mp ac t o f h i gh m ob i l i t y o f n o d es o n t h e d e t ec t io n accu r acy b y

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d i s t r i b u t i n g th e de t a i l o f f r i en d n od es an d m a l i c i ous n odes amo n g t he

f r i en d no d es . Th i s app r o ach s up po r t s t h e m an agem en t o f f a i rn es s b y

a l l o win g n o d es to p u b l i c l y d ec l a r e t he d e t a i l o f t h e i r f r i en d no d es and

b l ack l i s t ed ( m al i c i ou s ) no d es . T h e m aj o r n o t a t i on s u s ed i n t he

ap p ro ach o f Mi n imu m -T hr e sh o l d V a lue Bas ed J e l l yf i s h P e r i od i c D r op

A t t ack D et ec t i on A l go r i t hm ( M TV -JP D AD A ) a r e d es c r i b ed in T ab l e

3 . 1 . T h e o p er a t iv e p r o cedu r e o f p r o po s ed a l go r i thm MTV -J P D AD A i s

b a s ed o n th e f o l l ow i n g a s s um pt i on s :

1 . T h e s ou r ce n od e an d d e s t i n a t i on no de a r e con s id e r ed as t r us t ed

n o des . An d ev er y n od e m ai n t a i ns t h e F r i end sh i p T ab l e ( FT ) ,

M a l i c i ous Tab l e (M T ) and Beh av i o r M o n i t o r in g T ab l e (BM T ) .

In M T V -J P D A DA , e ach no d e p e r i od i ca l l y s en d s v e r y s h o r t ‘ H E LLO ’

m ess ages , t o d i s cov e r i t s o n e -h op n e igh b o r i n g no d e . A l l t h e no d es a r e

i n i t i a l l y p l aced in p ro mis cuo us mo d e . P r om is cu ou s m od es a r e a

s ecu r i t y p o l i c y t h a t en ab l es no d es to l i s t en t o im medi a t e no de

ac t i v i t i e s i n o rd e r t o m o n i t o r t he en t i r e n e t wo rk t r a f f i c . S o t o mo n i t o r

t h e comm un i ca t i on ac t i v i t i e s o f t he i r o n e -h op n e i ghb ors . E v e r y n o d e

m on i to r s t h e co r r ec t pack e t f o r wa r d i n g b eh av i o r o f i t s d i r ec t

n e i ghb o rs t h ro u gh p r omi s cu ou s mo d e . E ach n od e ma in t a in s F r i ends h ip

T ab l e , M a l i c i ou s T ab l e an d Beh av io r Mo ni t o r i n g T ab l e , fo r i t s

n e i ghb o rs .

F r i end sh i p T ab l e a t P ack e t Fo r w ar de r N od e co n t a i ns t h e d e t a i l s o f

f r i en ds ’ n od es ( t ru s t ed no d es ) o f Pack e t Fo rw ard e r N o d e to w hom

P ack e t Fo rw ar d er N od e can fo r wa r d t h e d a t a p ack e t s w i t ho u t

m on i to r i n g th e i r co mmu ni ca t io n ac t iv i t i e s . F r i en ds h ip T ab le ( FT)

co n t a i ns t h e ID s o f n od es , w h i ch a r e f r i en ds (e i t he r d i rec t f r i en ds o r

i nd i r ec t f r i en ds ) o f a n o d e . T h e da t a Fe l id s o f F r i endsh ip T ab l e ( FT )

a r e N OD E_ ID , F LA G S . ( i . e . D i r ec t o r i nd i r ec t f r i en ds ) .

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Table 3.1 Friendship Table (FT)

N O D E _ ID

F L AG S

M al i c i ous T ab l e (M T ) a t p acke t fo r wa r d e r no d e co n t a i ns t he m al i c io us

n o des (b l ack l i s t ed n od e ) de t ec t ed ( b a s ed o n p ack e t s , fo r w ar d i n g

b eh av io r ) b y p ack e t f o r w a rd e r no de t o wh om p ack e t fo r w a r d er no de

n e i th e r f o rw a r ds th e r o u t i n g and d a t a p ack e t s t h ro u gh t h em no r f rom

t h em. M al i c io us Tab l e ( MT ) s im pl y c o n t a i ns t h e ID s o f n od es w h ich

a r e b l ack l i s t ed b y t h e p ack e t f o r w a rd er no d e i t s e l f .

Table 3.2 Malicious Table (MT)

N O D E _ ID

Beh av i o r Mo ni t o r in g T ab l e ( BM T) a t p ack e t f o r wa r d er no d e co n t a ins

t h e ID s o f o n e - ho p n e i ghb o rs o f p ack e t f o r w ar d e r n o de w h os e b eh av i o r

a s f r i en ds ’ no d es o r m a l i c i ou s no des a r e s t i l l no t co nf i rm ed b y p ack e t

f o r w a rd e r n od e , and th e i r com mu ni ca t i on ac t iv i t i e s a r e s t i l l mo n i t o red

b y p ack e t f o r w a rd er no d e to co n f i rm t h e i r b eh av io r e i t he r a s a f r i end

o r as ma l i c i ou s no d es . Beh av io r Mo ni to r i n g Tab l e (BM T ) s imp l y

co n t a i ns t h e ID s o f n od es ( wh ich a r e n o t f r i en d ’s n od es ) t o k eep th e

r e co rd s o f t h e i r co r r ec t p ack e t s f o rw a r d i n g b eh av io r u s i n g a D rop

co un t e r ( D C) . Th e S econ d f i e lds i n BM T a r e M oni to r in g S t ep ( MS )

w h ich d e t e rmi n es th e s t age o f m on i t o r i n g n od e in a cco rd an ce wi t h the

v a lu e o f MS = 0 ( f i r s t t h e t im e ) and MS = 1 ( s econ d t h e t i me ) .

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Table 3.3 Behavior Monitoring Table (BMT)

N O D E _ ID

D r o p c o u n t e r

M o n i t o r i n g S t e p

In o r d e r t o h av e a c l e a r un d e rs t and in g o f t h e b as i c f un c t io n a l i t y o f

M in imu m Th r es ho l d V a l u e b as ed J e l l yf i s h P er io d i c D r o p At t ack

D e t ec t i on A l go r i t hm , th e app r oach i s d i v i ded in t o th e fo l l ow in g t h r ee

p h as e s .

Ph a s e1 : In t h i s p h as e , e ach no d e p e r i od i ca l l y s en d s v e r y s h or t

‘ H E LLO ’ m ess ages , t o d i s co v er i t s o ne - h op n e i ghb or in g n o de , and a l so

i n i t i a l i z es i t s f r i end sh ip t ab l e emp t y , m a l i c i ou s t ab l e em pt y , an d add

a l l on e -h op no de to t h e b eh av i o r m on i t o r in g t ab l es acco r d in g l y. A

r o u t e i s a l so es t ab l i sh ed b e t w een a so u r ce no d e and d es t in a t io n n od e

t o t r ans f e r t h e d a t a p ack e t s as p e r ba s i c r o u t e d i s cov er y p r o ce ss o f

A O D V r ou t in g p ro to co l . Th en ,

Fr i end sh i p T ab l e ( FT ) i s i n i t i a l i z ed . FT i s empt y u n l e s s t he

p ack e t s , fo r wa r d i ng p r o ces s i s s t a r t ed and fo r w ar d th e d a t a

p ack e t t o t h e n ex t r e ce iv e r n od e (N ex t S u ccess o r no d e) w i t ho u t

h a rm . A nd t h e Behav io r mo n i t o r i n g t ab l e ( BMT ) i s i n i t i a l i z ed b y

ad d i n g a l l i t s on e - h op no d es t o mon i t o r t h e i r b eh av io r us i n g

p r omi s cu ou s m od e an d ju d ge th e n od e i s m a l i c i ou s o r i nno cen t .

A t ev e r y p e r i o d i c i n t e rv a l , e ach n od e ch ecks t h e b eh av io r o f i t s on e -

h o p no des , an d d i s t r i bu t e T A BLE S - STA T E, wi t h t h e f o l l ow i n g f i e ld s :

T ABL ES –ST ATE [ PFN , f r i ends o f PFN , ma l i c i ous n odes o f PFN ]

Wh er e P ack e t F o rw ar d e r No d e i s t h e n od e Id o f T A B LE S -S TA TE

o r i g i n a t o r no de , f r i en ds o f P ack e t Fo r w ard e r N od e i s t h e l i s t o f

f r i en ds ’ n od es o f P ack e t Fo r war d er N o d e av a i l ab l e i n i t s f r i en ds h ip

t ab l e , an d m al i c iou s n od es o f P ack e t For w ard e r N od e a r e t h e l i s t o f

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m al i c io us no d es ava i l ab l e i n t h e m al i c i ou s t ab l e o f P ack e t Fo r w ard er

N o d e .

U p on rece i v i n g t he ,

T ABL ES - ST ATE [A ny on e N od e , f r i end s o f any on e nod e , ma l i c i ous

n od es o f an yon e no d e]

C on t r o l m es s age f ro m A n yo n e N od e (a f r i end n od e o f p ack e t f o r w a rd e r

n o de ) a t p ack e t f o rw a r d e r no d e , t h e pack e t fo r w a rd e r n od e up da t es i t s

FT , M T and BM T acco r d in g l y.

U s i n g Eq . 3 . 3 , w h i ch i s b as i ca l l y t h e l i s t o f t ho s e nod es w h i ch a r e

f r i en d no des o f a A n yo n e N o d e bu t P ack e t Fo r w ard e r Nod e h as a l r e ad y

co ns id e r ed th em as m al i c i ou s n od es . T h e en t r i es o f t he s e no d es a r e

ad d ed aga i n i n t h e b eh av io r a l m on i to r i n g t ab l e o f P acke t Fo r w ar d er

N o d e b y r em ov in g t h e i r en t r i e s f r om t h e M al i c io us T ab l e o f P ack e t

Fo r w ard e r N od e . T h e en t r i e s o f t h e s e no d es a r e ad d ed t o t h e

b eh av io r a l mo n i t o r i n g t ab l e o f P ack e t Fo r w ar d er N o de w i th th e i r DC,

M S eq u a l t o 0 , 0 .

Malicious PFN Node Anyone of Friends =ceAcquaintan _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 3.3

U si n g Eq . 3 .4 s how s t h e f o r mu la used i n u pd a t in g the FT a t no d e

P ack e t Fo r w ar d e r N o d e . I f an y n o de i n t h e Beh av io ra l Mo ni t o r in g

T ab l e o f P ack e t Fo r w ard e r No d e an d f r i en ds o f P ack e t Fo r w ard er

N o d e , t h en th e en t r y o f t h e r e sp ec t ive n o d e wo u l d r emo v e f ro m th e

Beh a v i o ra l M o ni t o r i n g T ab l e o f no d e P ack e t Fo rw ard e r N o d e .

ceAcquaintan

Node Anyone PFN of FriendsPFN of Friends

_ _ __ __ __ __ __ __ ___ _ __ __ 4.3

Ph a s e2 : In t h i s phas e , ev e r y i n t e rm ed i a t e n od e ch ecks t h a t t h e N ex t

S u ccess o r N o de ( N S N) i s p r es en t i n i t s FT in o rd e r t o fo r w a rd th e

D a t a P ack e t s . I f i t i s p r es en t t h e r e ( i n t h e FT ) , t h e d a t a i s f o r wa r d ed

t o NS N w i th ou t m on i to r i n g t h e ac t i v i t i e s o f t h e n o de t h ro u gh

p r omi s cu ou s m od e . I f N S N i s p r es en t i n t h e M T t ab l e , t h en a R ou te

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e r r o r mess age wi l l b e s en t t o t he s ou r ce no d e .

Ph a s e3 : Th i s p h ase co m es in t o t h e p i c t u r e o n l y w h en N ex t Su cces so r

N o d e) N SN i s n o t p r e s en t i n t h e FT an d MT t ab l e s . T h e f o l l ow in g

s t ep s a r e p e r fo r med in t h i s p has e . Th e NS N i s s ea r ch ed in i t s BMT

( i . e . w h e th e r i t i s p r e s en t t h e r e o r n o t ) .

I f N S N i s f ou nd i n i t s BMT , i t c h ecks M on i t o r in g S tep ( MS ) v a l u e o f

N S N an d th e v a l u e m us t be l e s s t h an to 1 .

IF M S > 1 S en d R ou t e E r r o r t o t h e S our ce N od e . IF M S <= 1 th en ch eck

D r o p C ou n t e r v a lu e i s l e s s t h an t h e Min im um th r es ho ld va l u e .

IF t h e D r o p C ou n t e r v a lu e i s g r ea t e r t h an th e MT V , t h en i n c r em en t t h e

v a lu e o f M oni to r i ng S t ep s (MS ) b y 1 an d co n t in ue f o rw ar d in g t he d a t a

p ack e t s . A ga in , check D r op Co un t e r v a lu e i s g r ea t e r t h an t h e MT V

t h en S en d R ou t e Er r o r m es s age f o r t h e s eco nd t i me t o t h e s o u r ce n od e

an d A dd N ex t S u cces so r N od e ( NSN) to t h e M T o f pack e t f o r w a rd

n o de . Ot h e rw i s e , s en d th e D a t a P ack e t t o N ex t S u ccess o r N od e ( NS N ) .

IF t h e Dr op C oun t ( DC ) to a sma l l e r ex t en t t h an th e m in i mum

t h re sh o l d v a lu e f o r w a rd t he D a t a p ack e t s and r em ov e t he Nex t

S u ccess o r No d e f rom BM T o f i t s e l f add t o i t s F r i en ds h i p T ab l e .

I f N ex t S u ccess o r N o d e i s no t p r es en t i n i t s BMT , t h en ad d t h e Nex t

S u ccess o r N od e to t h e BMT o f p acke t f o rw a rd e r no d e w i t h t h e v a l u e

D r o p C ou n t e r = 0 an d MS = 0 .

In gen e r a l , t h e p r oce d u re s fo l lo w ed in ou r MT V -J PD AD A l go r i t hm i s

i l l u s t r a t ed i n F l o w C h ar t 3 .1 an d ps eud o co d e 3 .1 :

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Figure 3.1 Proposed MTV-JPDADA flow chart

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Algorithm 3.1: MTV-JPDAD Algorithm

A l g o r i t h m 1 : M i n i m u m t h r e s h o l d V a l u e B a s e d J e l l y f i s h P e r i o d i c Dr o p

A t t a c k De t e c t i o n A l g o r i t h m ( M T V - J P DA D A)

R e q u i r e s :

S r c : S o u r c e No d e

D s t : De s t i n a t i o n No d e

P F N : P a c k e t F o r wa r d e r No d e

M TV: M i n i mu m T h r e s h o l d V a l u e

N S N : Ne x t S u c c e s s o r N o d e

T r 1 : T h r e s h o l d V a l u e 1

M S : M o n i t o r i n g S t e p

D C : D r o p Co u n t

F T: F r i e n d s h i p T a b l e

M T : M a l i c i o u s T a b l e

B M T : Be h a v i o r a l M o n i t o r i n g T a b l e

B e g i n

F o r a l l n o d e s i n t h e n e t w o r k D o

I n i t i a l i z e BM T wi t h n o d e s l i ke a s u s p e c t e d p e r s o n i n t h e r e a l wo r l d .

I n i t i a l i z e F T , M T a n d BM T t a b l e f o r a l l n o d e s i n t h e n e t wo r k .

S h a r d F T a n d M T w i t h n o d e s ma i n t a i n e d i n t h e i r F T a n d M T a n d U p d a t e

a c c o r d i n g l y .

E n d f o r

F o r e a c h p a c k e t p f o r wa r d e d b y a n o d e , P F N d o

I F NS N e l e me n t o f f r i e n d s o f a P F N ( i . e . N S N i s p r e s e n t i n F T P F N) t h e n

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P F N f o r w a r d s t h e p a c ke t d i r e c t l y t o t h e N S N t o b e f o r wa r d e d f u r t h e r

E l s e I f t h e NS N e l e me n t o f P F N a s a ma l i c i o u s n o d e ( i . e . T h e N S N i s p r e s e n t

i n M T P F N) t h e n

P F N s e n d Ro u t e E r r o r M e s s a ge ( R E R R) t o t h e S R C a n d D i s c a r d t h e

p a c ke t .

S R C i n i t i a l i ze a r e - r o u t i n g d i s c o ve r y p r o c e s s u s i n g t h e d e f a u l t A O DV

r o u t e d i s c o v e r y P r o c e s s .

E l s e

I f N S N n o t a n e l e me n t o f P F N . BM T ( i . e . N S N n e w t o t h e B M T o f n o d e

P F N) t h e n

I n s e r t Ne x t S u c c e s s o r N o d e t o P F N o f BM T

In i t i a l i ze D C = 0 , M S = 0 i n BM T o f P a c k e t F o r wa r d e r N o d e

An d F o r wa r d t h e Da t a P a c k e t

E l s e

T h e N S N e l e me n t o f P F N. BM T ( i . e . T h e NS N i s a l r e a d y p r e s e n t i n

B M T o f n o d e P F N)

I f M o n i t o r i n g S t e p > 1 t h e n

Ad d N e x t S u c c e s s o r No d e t o M T o f P F N

P F N s e n d Ro u t e E r r o r M e s s a ge ( R E R R) t o t h e S r c a n d

D i s c a r d t h e p a c ke t .

E l s e

I f ( Dr o p Co u n t e r v a l u e > M i n i mu m T h r e s h o l d V a l u e ) t h e n

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M S = M S + 1

F o r wa r d t h e Da t a P a c k e t

E l s e

Re mo ve N S N. BM T a n d a d d t o NS N. F T

F o r wa r d t h e Da t a P a c k e t

En d i f

En d I f

En d i f

E n d i f

E n d f o r

E n d

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Chapter 4 Implementation and Performance

Evaluation

4 .1 Implementat ion and Performance Metrics Analys is

W e h av e i d en t i f i ed p e r fo rm an ce m et r i c s us e fu l t o co mp a re th e se l ec t ed

r o u t i n g p ro t o co l s by e v a l u a t i n g n o rm al A OD V n e t wo rk scen a r i os wi th

J e l l yf i s h p e r i od i c d r op At t ack an d M in imu m J e l l yf i s h p e r i od i c d r op

a t t a ck d e t ec t i on a lgo r i t hm im pl em en ted i n A OD V n e t wor k s cena r i o .

4 .1 .1 Attack Detect ion Rate

I t i s d e f i n ed a s t h e r a t i o o f t h e nu mb er o f m al i c io us n odes d e t ec t ed to

t h e t o t a l n um b er o f ex i s t i n g m al i c io us n od es i n t h e n e t wor k .

100*usNoderOfMalicioTotalNumbe

odeMaliciousN DetectedctionRateAttackDete

% _ _ _ _ _ _ _ _ _ _ _ _ _ _ 5.3

4 .1 .2 False Negat ive Rate (FN R)

I t i s d e f i n ed a s t h e r a t i o o f t he nu mb er o f m al i c i ous o nes b e in g

d e t ec t ed a s no rm a l n o d es to t he t o t a l n u mb e r o f n o rm al n o d es in t he

n e tw o rk .

100*oderOfNormalNTotalNumbe

esNormalNodeDetectedAliciousNodNumberOfMaiveRateFalseNegat

% _ _ _ 6.3

4 .1 .3 False Pos i t ive Rate (F PR)

I t i s d e f in ed as t h e r a t i o o f t he n um ber o f no r ma l on es b e in g d e t ec t ed

a s m al i c io us n od es t o t h e t o t a l n um b er o f m al i c io us n o d es in t he

n e tw o rk . In t h i s d e t ec t io n a l go r i th m, t h e Fa l s e Po s i t i v e ra t e i s n ea r t o

z e ro b ecau s e t h e p ack e t d r op p ed b e l o w t h e mi n im um th r esh o l d v a lu e i s

a l l o w ed and co ns ide r ed a s a s us p ec t ed n od e , n o t an a t t a ck e r N od e .

100*usNoderOfMalicioTotalNumbe

eliciousNodtectedAsMarmalNodeDeNumberOfNoiveRateFalseNegat

% _ _ 7.3

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4 .1 .4 Average End - to -End De lay

I t i s d e f i n ed a s t h e t im e t ak en f o r a d a t a p acke t t o b e t r ans mi t t ed

ac r o ss a M A NE T f ro m so u rce t o d es t i na t i on [ 1 2] .

ondsecReceivedPacket No.

TimeSent - Time ReceivingDelay End To End _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 8.3

4 .1 .5 Packet Del ivery Rat io (Frac t ion)

I t i s c a l cu l a t ed b y d i v i d in g t h e n um b er o f p ack e t s r e ce iv ed b y

d e s t i n a t i on i n t h e nu mb er o f p ack e t s o r i g in a t ed f r om th e s ou r ce .

SentPacket

ReceivedPacket RatioDelivery Packet % _ __ __ __ __ __ __ __ _ __ __ __ __ __ _ 9.3

4 .1 .6 Throughput

I t i s t h e r a t i o o f t h e to t a l nu mb e r o f b i t s t r ansm i t t ed (B tx ) du r i n g a

g i v en t r ansm iss io n t im e , i . e . t h e d i f fe r en ce o f d a t a t r an sm iss io n en d

t im e ( Tend ) an d s t a r t s t im e ( Ts t a r t ) . T h i s m e t r i c d ep i c t s ho w th e

co n ges t i on co n t r o l m ech an i s m a t t h e s ou r ce n od e i s a f f ec t ed b y t h e

p ack e t l o s s es c au sed b y J e l l yf i s h pe r i od ic d ro p n od es . A d ec r eas e i n

t h ro u ghp u t i s an o u t com e o f an y J e l l yf i sh p e r i od i c d r op a t t a ck [ 12] .

bpsTimeStart - Time End

ed transmittbitsThroughput _ _ __ __ __ __ __ __ ___ _ __ __ __ __ __ 10.3

4 .2 Simulat ion Tools

T h e s i mul a to r , wh ich i s u s ed fo r s i mul a t io n i s NS 2 . W e h av e a l so us ed

E c l i ps es , G N U P lo t and NS G2 .1 t oo l s a s d e s c r ib ed b e lo w: U s in g th e se

t oo l s , w e h av e i mpl em en t e d ou r d e t ec t io n a l go r i th m and an a l yz ed i t s

p e r f o r man ce im pac t o n TC P . T o ev a l ua t e t he pe r f o r m an ce o f a p r o t o co l

f o r an Ad Ho c n e tw o r k , i t i s n eces s a r y t o an a l yz e i t un d e r p r ac t i c a l

co nd i t i on s , e sp ec i a l l y i n c l ud i n g th e m ov em ent o f mo b i l e no d es . T h e

s im ul a t i on r equ i r es s e t t i n g u p t r a f f i c , mu l t i p l e con n ec t i on and

m ob i l i t y m o d e l f o r p e r f o r man ce ev a lu a t io n .

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4 .2 .1 NS2

F i r s t , s imu l a t i on re f e r s t o a r e a l - wo r l d s ys t em w hi ch i s i mi t a t ed v i a

co mp ut a t i on a l r e - en ac tm en t o f i t s beh av i o r s ba s ed o n r u l es i n a

m at h em at i ca l fo rma t . S im ul a t io n i s u s ed i n o r d er t o a l l o w s a f e r and

ch eap er t e s t i n g , o p t imiz e s ys t em p e r f o r man ce , and ev a lu a t e t h e

ad v an tages and d i s adv an t ages o f t h e m e th od . Becau s e t h e n a tu r e o f

co mp ut e r comm u ni ca t io ns an d n e tw o r k mo d e l s a r e co mpl ex , t he

d ev e l opm ent o f spec i a l com pu t e r p r ogr am s f o r a sp ec i f i c s i mul a t io n

i s s u e i s a po ss i b i l i t y , b u t t o t a l l y i n e f f i c i en t an d t im e - co ns um in g . Wi th

t h e i mp ro v em ent i n t h e ap p l i c a t io n o f m od e l in g p ack ages an d

s im ul a t i on s , t h ey h av e b ecom e t im e -sav in g i n t he a r ea o f cod in g an d

m o re cu s to m ar y w h i ch en ab l es p ro gramm er s t o fo cus on t h e m od e l in g

p r ob lem r a t h e r t h an t h e p ro gr ammi n g d e t a i l s . M an y n e t wo r k s im ul a t o r s

a r e av a i l ab l e t o u s e su ch a s Cn e t , OM N ET ++ , N e tS i m, OPN E T,

Q u a l N et , Glo MoS im , N S2 , and NS 3 . In t h i s s tu d y, N S 2 i s u s ed f o r t wo

m ai n rea so ns . F i r s t , t h e m a jo r i t y o f s tu d i es o n l in e u se t h i s t oo l t o

s im ul a t e t h e i r p ro to co l s wh i ch d em ons t ra t es i t s go o d r epu t a t i on i n t he

r e s ea r ch co mmu ni ty . S eco nd , mu ch do cum ent a t i on i s ava i l ab l e o n l i n e

w h ich a l l ev i a t e s t h e d i f f i cu l t y o f t h e l e a r n i n g p ro cess and cod in g .

H o w ev e r , a s e l ec t i on c r i t e r i o n f o r t h e n e t wo rk s im ul a t io n in c l ud es

m an y f ac t o r s ; f o r ex ampl e , so f t w a r e l i c en s e co s t s . NS 2 i s f r e e an d o ne

o f t he m os t p ow er fu l t oo l s w h i ch can b e u s ed in n e t w or k r e s ea r ch and

d ev e l opm ent .

T h e r e a r e c e r t a i n ad v an tages t o u s i ng N S 2 to s im ul a t e n e tw o rk s a nd

p r o t oco l s . F i r s t , i t i s cos t - f r e e and do es no t r eq u i r e ex t r a eq u i pm en t .

U s u a l l y , i t ru ns o n a Li n ux p l a t fo rm o r us ed wi t h t h e Cyg w i n p r o gram

o n a Wi nd ow s p l a t f o rm. S eco nd , co mpl i ca t ed s cen ar i os c an b e

s im ul a t ed an d t es t ed eas i l y . T h i rd , i t i s a p op u l a r s i mul a t o r a s r es u l t s

c an b e o b t a i ned qu i ck l y an d m an y i d ea s c an b e t e s t ed wi t h i n a sm al l e r

t im e f r am e . In ad d i t i o n , N S2 i s co ns id e r ed as a s t an d ar d ex p e r i m en t a l

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en v i ro nm ent i n t he r e s ea r ch comm un i t y . T h e us e o f t h e s im ul a t o r

p r ov id es an o pp or tu n i t y t o i nv e s t i ga t e an d u nd e rs t and th e d yn am i cs o f

n e tw o rk s . NS2 p r ov id e s su bs t an t i a l su p po r t , i n o r d er t o s im ul a t e m an y

p r o t oco l s , s uch a s FT P , T CP , U DP , DSR , and H TT P. Bes id e s , NS 2 i s

u s ed to s i mul a t e bo th w i r ed an d wi re l es s n e t wo rk s . TCL i s t he m ai n

s c r i p t i n g l an gu age , w h i ch i s O b j ec t -o r i en t ed su pp or t ( o t c l ) . NS 2 u s es

t w o l an gu ages : TC L s c r i p t an d C++ . Th e r eas on fo r us in g t wo

l an gu ages i s t h a t T C L s imu l a t es s om e s l i gh t l y v a r yi n g p a r am e t e r s o r

co n f i gu r a t i on s , such a s q u i ck ex p lo r e o f s cen a r i o n um b er s an d

i t e r a t io n t im e .

Fu r th e rm o re , t h e s i mul a to r ha s v a r iou s t yp es o f t a s ks t o un de r t ak e .

F i r s t , i t n eed s a p ro gr amm in g l an gu age t o m an i pu l a t e b yt e s e f f i c i en t l y

o r ev en p ack e t h ead e r s w h i ch r un ove r l a r ge d a t a w h ere t he r un - t im e

s p eed i s mo r e es sen t i a l an d t he tu rn ro u nd t i m e i s o f l ow im po r t an ce .

T h us , C ++ i s f as t t o ru n , b u t s lo w t o ch an ge whi ch m ak es i t mo r e

s u i t ab l e f o r d e t a i l ed p r o to co l imp l emen t a t i on . S eco nd , a g r ea t p a r t o f

t h e ne tw o rk in c lu des ex p lo r i n g a n umb er o f s cen a r io s qu i ck l y a s r u n -

t im e sp eed h a s l e s s imp o r t an ce . How ev e r , C ++ s im ula t es p r o to co l

r eq u i r em en t s su ch a s p ack e t p r o ce ss ing , a l go r i th m i mpl em en t a t i on , r un

s im ul a t i on , r e r un , r e co mpi l e , an d ru n t i me sp eed . Th a t OT c l ru ns m o re

s lo wl y b u t c an b e ch an ged q u i ck l y m ak es i t ap pr op r i a t e f o r s ys t em

co n f i gu r a t i on .

4 .2 .2 Ecl ipses

In N o v emb er 2 00 1 , a co ns or t iu m w as fo rm ed b y IBM t o su pp o r t t h e

d ev e l opm ent o f t he E c l ip s e ID E a s o p en so ur ce s o f t wa r e . In 2 0 04 i t

b ecam e th e E c l ip s e Fo u nd a t io n , w h i ch i s a v end or - n eu t r a l fo un d a t i on

w h e r e no s in g l e com p an y h a s con t ro l o f t he d i rec t io n .

T h e E c l ip s e Fo un da t i on i s a n on -p r o f i t , m em ber su pp or t ed co rp or a t ion .

I t h e l p s t o cu l t i v a t e b o t h i t s op en s our ce comm un i t y an d i t s e cos ys t em

o f com pl em en t a r y p r od u c t s an d s e r v i ce s .

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T h e m is s io n o f t h e E c l i ps e Fo un d a t i on i s t o en ab le t h e dev e lo pm e n t b y

p r ov id i n g th e in f ra s t r u c t u r e ( v e r s i on co n t r o l s ys t ems , co d e r ev i ew

s ys t ems , bu i ld s e rv e r s , t h e d ow nl oad s i t e s , e t c . ) an d a s t r u c tu r ed

p r o cess . Th e Ec l i ps e Fou nd a t io n do es no t wo rk on th e E c l i ps e co de

b a s e , i . e . , i t do e s n o t h av e emp lo yee d ev e l op e rs w o rk in g o n E c l ip se

p r o j ec t s . E c l i ps e p r o j ec t s f o l l o w a v e r y w e l l d e f i n ed dev e l opm ent

p r o cess d es c r i p t i on . A nd w e a r e us in g th i s t oo l f o r co mpi l i n g t he

A O D V p ro t o co l .

4 .2 .3 GNU Plot

G N U p l o t i s a f r e e , com m an d - d r i ven , i n t e r ac t i ve , f u n c t io n an d d a t a

p lo t t i n g p r o gr am . G N U p lo t can ru n u n de r D OS , Wi nd ow s , Mac in t osh

O S , BeOS , OS2 , V MS , Li n ux , an d m an y o t h er s . O n Unix / Li nux

s ys t ems s t a r t GN U p lo t b y s i mpl y t yp i n g : G nu p lo t

4 .2 .4 Aho, Weinberger , and Kernighan S cr ip t s

A WK i s a s c r i p t in g l an gu age used f o r m an i pu la t i n g d a t a and

gen e r a t i n g r ep or t s . T h e AW K com mand p ro gr ammi n g l an gu age

r eq u i r es no com pi l i n g and a l lo w s th e u s e r t o u s e v a r i ab l es , n um er i c

f u n c t i on s , s t r i n g fun c t io ns , and l o gi ca l o p er a to r s .

A WK i s a u t i l i t y t ha t en ab l es a p r o gr am mer t o w r i t e t i n y b u t e f f ec t iv e

p r o gr am s in t h e f o rm o f s t a t em en t s t ha t d e f i n e t ex t p a t t e r n s t h a t a r e t o

b e sea r ched fo r i n e ach l i n e o f a do cum ent an d th e ac t i on th a t i s t o be

t ak en w h en a m a tch i s f ou nd w i th in a l i n e . AW K i s mo s t l y u s ed f o r

p a t t e rn scann in g and p ro ce ss i n g . I t s e a r ch es o ne o r m or e f i l e s t o s ee i f

t h ey co n t a i n l i n es t h a t m at ch t he s p ec i f i ed p a t t e rn an d t h en p e r fo rms

t h e as so c i a t ed ac t io ns .

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4 .2 .5 NSG2.1

N S2 S cena r ios G en e r a t o r 2 (NS G 2) i s a J A V A - b as ed n s2 s cen ar io

gen e r a to r . S i n ce NS G2 i s w r i t t en b y J A V A l an gu age , yo u can r u n NSG

o n an y p l a t f o r m. N S G2 i s c apab l e o f gen e r a t in g b o t h wi r ed and

w i r e l es s TC L s c r ip t s f o r NS 2 .

4 .3 Resul ts and Discuss ions

4 .3 .1 Ex per imenta l Des ign and Scenar io for Je l ly f i sh Per iod ic

Drop Attack

In t h i s ex p e r im en t , t h e J e l l yf i s h p e r io d i c d ro p a t t a ck i s o ccu r r in g , i n

o r d e r t o t e s t t h e p e r f o rm ance o f t h e in f ec t ed n e t w or k s i t ua t i on , a s w e l l

a s de t e r mi ne ho w th e n e t wo rk i s d egrad ed in t h i s s i t u a t io n u s in g N S2 .

W e us e U BU NT U 1 2 .0 4 Op e r a t i n g s ys t em b ecaus e gcc4 .4 an d g++4 .4

i s t h e sam e w i th NS 2 . 35 s im ul a to r and i t s s t ab l e i n t h i s Li n ux v er s ion

an d be lo w ve r s ion . Th e s im ul a t i on p a r am e t e r s an d t h e com pu t e r

s p ec i f i c a t i on s , w h ich a r e u t i l i z ed in t h i s ex p er im en t , a r e s ho wn in

T ab l e 4 .1 .

Table 4.1 Simulation parameters

S i m u l a t i o n p a r a m e t e r s

P r o c e s s o r I n t e l ( R) C o r e ( T M ) i 7 -4 5 0 0 U C P U @ 1 . 8 G H z ( 4 C P Us )

R AM 6 . 0 0 GB

S y s t e m t y p e 6 4 -b i t

O p e r a t i n g s ys t e m U B U NT U 1 2 . 0 4

R o u t i n g p r o t o c o l A O DV

S i mu l a t i o n t i me 4 0 mi n

N o o f n o d e s 5 , 1 0 , 1 5 , 2 5

T r a n s p o r t P r o t o c o l T C P

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T r a f f i c t y p e F T P

P a c ke t s i ze 5 1 2 b y t e s

M AC t yp e M a c / 8 0 2 _ 1 1

A r e a 8 0 0 m x 8 0 0 m

M o b i l i t y s p e e d s M i n 1 , M a x 1 0 m/ s

Fi gu r e 4 . 1 Sh o w t h e n e t w or k a r ch i t e c t u r e t h a t i s u s ed to t e s t t he

n o rm al Ad Ho c ne t wo r k b e fo r e t h e a t t a cks o ccur . Mo r eov e r , ev er y

a t t a ck i s app l i ed a s a s e p a r a t e ex p e r i men t . Th e m ai n a r ch i t e c tu r e o f

t h e n e t w or k fo r t he ex p e r im en t s i s t h e s am e, a s i t i n c lu d es 5 , 1 0 , 15

an d 2 5 n od es , i n c l ud in g s ou r ce n od e an d de s t i n a t i on no d e . W e can a l so

i n c r ea s e t h e nu mb er o f no d es as w e wan t . Fo r t h i s s cena r i o w e us e t h e

n um b er o f n od es r an d oml y m i n im um 5 , m ax imum 25 . I t i s imp o r t an t t o

m en t i on th a t t h e re a l - t i m e s ch edu l e i s u s ed i n t h e s i mu l a t i on w hich

h e lp s t o s yn ch r on i ze th e ex ecu t i on o f ev en t s wi t h r e a l - t im e . F i gu re 4 .1

s ho w s t h e a r ch i t e c t u r e o f M A NET s w i th ou t a t t a ck . T h e ma in

a r ch i t ec tu r e o f t h e n e t w or k f o r t h e ex p e r im en t s i s p l ac i n g t h e no d es

r an dom an d m ak es t h em mo bi l e and th e mi n im um s peed an d max i mum

s p eed a r e t o 1 , 10 m /s r es pec t iv e l y, t h e no d es m ov e r and om l y w i t h t h e

g i v en d i am e t e r , and th e r e a r e m ul t ip l e co nn ec t i on in t h e n e tw o rk 1 up

t o 7 , t h e t o t a l nod es a r e 5 , 1 0 , 15 , 2 5 in c l ud in g s ou r ce n od e and

d e s t i n a t i on no d e . T h e d u r a t i on o f t h i s ex p e r i m en t i s 4 0 m in u t es .

Becau s e t o i s o l a t e t h e m al i c i ou s no d e f ro m t h e n e tw o r k t im e i s

r eq u i r ed t o mo n i t o r and ob se r v e th e beh av i o r o f t h e p acke t fo r w ar d i n g

n o de .

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Figure 4.1 AODV with 25 normal nodes

F i gu r e 4 . 2 Sh o w th e a r ch i t e c t u r e o f M A NE Ts w i th J e l lyf i s h p e r i od i c

d r op a t t a ck i n t ro duced . A nd h as 5 u p to 25 n od es .

Figure 4.2 AODV 25 nodes with JPD Attack

A f t e r t he ab ov e scen a r i o , t h e n e t wo rk i s d egr ad ed b y a l l m e t r i c s as

s ho w n i n t h e g r aph b e lo w. A nd w e can u nd e rs t and h ow t h e J e l l yf i sh

p e r i od i c d r op a t t a ck can b e m ak in g our n e t wo r k i ns i gn i f i c an t .

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4 .3 .2 Resul t s and Evaluat ion s aga ins t Je l ly f i sh Per iodic Drop

At tacks

T h e ne tw o rk p e r fo r man ce i s m eas ur ed in t w o ev a l ua t i on m et r i cs :

p ack e t d e l i v e r y r a t i o , an d A v er age th r ou gh pu t . Su bseq u en t l y, t he

n e tw o rk p er f o r m ance f o r e ach a t t a ck i s m easu r ed f o r 4 0 mi nu t es .

Becau s e t o i s o l a t e t h e m al i c i ou s no d e f ro m t h e n e tw o r k t im e i s

r eq u i r ed t o mo n i t o r and ob se r v e th e beh av i o r o f t h e p acke t fo r w ar d i n g

n o de . T h e r ea so n f o r t h i s m eas ur em en t i s t o com p a re t he p e r f o rm an ce

o f t h e n e t wo r k in t w o s i t u a t io ns : b e fo r e t h e o ccu r ren ce o f t h e a t t ack

an d a f t e r t h e a t t a ck o ccu r s .

A f t e r an a l yz i n g th e ex p er im en t i s t h e s cen ar io t h e A v er age t h ro u ghp u t

o f t h e n e t w or k i s h i gh l y d egr ad ed a s sh o wn i n t he n e t wo rk F i gu re 4 . 3 .

S om eh o w, as t h e nu mb er o f n od e i n c rea s e s t h ro u ghp u t o f t h e ne tw ork

i s d ec r eas ed , wh en co mp ar ed wi th the n o rm al n e t wo r k a f t e r s om e 10

n o des i t s ho w b e t t e r t h r ou gh pu t . A f t e r - a l l t h e t h r ou gh p u t o f t h e

n e tw o rk d egr ad ed .

Figure 4.3 Average Throughput of MANETs

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J e l l yf i s h p e r i od i c d r op a t t a ck mi n imiz es t h e p ack e t d e l iv e r y r a t i o as

s ho w n in F i gu re 4 .4 . Becau s e th e gene r a t ed p ack e t t h a t w as t oo sen t i s

d r op p ed b y t h e a t t a ck . As t h e num b er o f p ack e t s d r op ped to i n c r ease

t h e p ack e t d e l iv e r y r a t i o i s h i gh l y d egr ad ed i n t h e n e t wo rk .

Figure 4.4 Packet Delivery Ratio

4 .3 .3 Ex per imenta l Des ign a nd Scenar io for MTV-JPDADA

In t h i s ex pe r im en t a l s cen a r i o , J e l l yf i sh p e r i od i c d r op a t t a ck and i t s

d e t ec t i on m ech an i s m M in i mum T hre s ho ld V a l u e b ased J e l l yf i s h

P e r i od i c D ro p At t ack a r e im pl emen t ed , i n o r d er t o t e s t t h e

p e r f o r man ce o f t he i n f ec t ed n e t w or k , a s w e l l a s d e t e rm in e ho w th e

n e tw o rk i s u p gr ad ed w h en t he d e t ec t ion m ech an i sm i s p r es en t ed i n t h i s

s i t u a t io n . A s d emo ns t ra t ed in t h i s s ec t i on , t h i s ex p e r im en t us e s t h e

s ame n e t wo r k s im ul a t o r . Th e s imu l a t io n p a r am et e r s and t h e com put e r

s p ec i f i c a t i on s , w h ich a r e u t i l i z ed in t h i s ex p er im en t , a r e s ho wn in

T ab l e 4 . 1 ab ov e .

F i gu r e 4 . 5 Sh o w t h e n e t w or k a r ch i t e c t u r e t h a t i s u s ed to t e s t t he

D e t ec t i on Al go r i t hm a f t e r t h e J e l l yf i s h p e r i od i c d r op a t t a ck o ccu rs .

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T h e m ai n a r ch i t e c tu r e o f t h e n e t w or k f o r t h e ex p e r i men t s i s p l ac in g

t h e no d es r an dom an d m ak es th em mo bi l e and t he m in im um s p eed an d

m ax im um s p eed a re 1 , 1 0 m/ s r e sp ec t iv e l y , t h e n od es m ov e r an do ml y

w i t h th e g iv en d i am et e r , and t h e r e a r e m ul t ip l e conn ec t io n in t h e

n e tw o rk 1 up t o 7 , t he t o t a l no d es a re 5 , 10 , 1 5 , 2 5 i n c l ud in g so u rce

n o de an d d es t in a t io n n od e . W e can a l so i nc r ea se t h e num b er o f no des

a s w e w an t . Fo r t h i s s cena r io we use th e n um b er o f no d es r an do ml y

m in i mum 5 , m ax imu m 25 .

F i gu r e 4 . 5 S ho ws t h e a r ch i t e c tu r e o f M A N ET s a t t a ck w i t h m in i mum

t h re sh o l d v a l u e b a s ed J e l l yf i s h pe r io d i c d r op a t t ack d e t ec t i on

a l go r i thm . An d h as 5 , 10 , 15 and 25 n od es an d th e du r a t io n o f t h i s

ex p e r im en t s cen a r io i s 4 0 mi nu t es . Becau s e to i so l a t e t h e m al i c i ou s

n o de f ro m th e n e tw o r k t im e i s r eq u i r ed t o mo n i t o r and ob s er v e th e

b eh av io r o f t h e p ack e t fo r w a rd in g no de .

Figure 4.5 AODV with Attack

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4 .3 .4 Resul t s and Eva luat ion s against Min imum Threshold

Value based Je l ly f i sh Per iod ic Drop At tack Detec t ion

Algor i thm (MTV-JPDADA )

T h e n e t wo rk p e r fo r man ce i s m eas ur ed in s ix ev a l u a t io n m et r i cs :

A t t ack D et ec t i on R a t e , Fa l s e N ega t i v e R a t e , Fa l s e Po s i t i v e R a t e ,

A v e r age Th r ou gh pu t , P ack e t D e l iv e ry R a t i o , an d En d t o E nd D el a y .

S ub sequ en t l y, t h e n e tw o rk pe r f o r m ance f o r each a t t a ck w as m eas u r ed

f o r 4 0 mi nu te s . Becau s e to i so l a t e t h e m a l i c i ou s n o de f ro m th e

n e tw o rk t im e i s r eq u i r ed t o m on i to r an d ob s er v e th e b eh av i o r o f t he

p ack e t f o r w a rd in g n o d e . A l l s im ul a t io n s cen ar io s a r e t ak in g a

s ampl in g f r om 10 d i f f e r en t s i mu la t i on r es u l t s a s an av e r age . T he

r ea s on fo r t h i s meas u rem en t i s t o co mp a r e th e p e r f o r m an ce o f t h e

n e tw o rk a f t e r t h e o ccu r r en ce o f t he a t t a ck an d a f t e r p l ac i n g t he

d e t ec t i on a l go r i thm . No w, th e t wo - f ac t o r m eas ur ed i n p r ev i ous

ex p e r im en t s : ne two r k Th r ou gh pu t , an d Pack e t D e l ive r y R a t i o a r e

co mp a r ed b e t w een t h e a t t a ck ed an d de t ec t ed s cen ar io o f t h e J e l l yf i sh

p e r i od i c d r op a t t a ck s . A l s o , o t h e r im po r t an t m et r i cs : At t ack D et ec t ion

R a t e , Fa l s e N ega t i v e R a t e and , Fa l s e Po s i t i v e R a t e a r e t ak en t o

m eas u r e th e o v era l l pe r f o r m an ce o f t h e d e t ec t io n a l go r i thm . T h e

r ea s on f o r t h i s com p ar i s on i s t o eva l u a t e t h e p r op os ed m e th od o f

e f f ec t iv en ess u nd er d i f f e r en t a t t a ck s cen ar io s . Th e s imu l a t i on r es u l t s

f o r N e t w o rk T hr ough p u t , P ack e t D e l iv e r y R a t i o , E nd t o En d D el a y

R a t io ; D e t ec t io n Ra t e , Fa l s e N ega t iv e R a t e and , Fa l se Po s i t i v e R a t e i s

s ho w n in F i gu r e 4 . 6 , F i gu r e 4 . 7 , 4 . 8 , 4 .9 , 4 . 10 and F i gur e 4 . 1 1

r e s p ec t iv e l y.

A s s ho w n in F i gu re 4 .6 t h e D e t ec t i on R a t e i s w i t h go od accu r acy. In

a l l s c en a r i o s , m a l i c i ou s n od es a re ex ami n ed and ju d ged a s an a t t a ck er

n o de . M a l i c i ous n od e i s ex ami ned b y a d r op p ed d a t a p ack e t , measu r ed

b y t h e m i n im um th r e s ho l d v a lu e ( M TV ) . I f a n o d e ’s d r op d a t a p ack e t ’ s

b eh av io r i s g r ea t e r t h an th e M TV v a l u e , t h e MT V -J PDA D a l go r i t hm

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co ns id e rs t h e n ode a s an a t t a ck e r n o de . T ab l e 4 .2 d e s c r ib e s t h e

an a l ys i s o f t h e de t ec t io n r a t e s cena r io t h a t w as ex am in ed i n t he

o ccu r r en ce o f 1 u p to 5 a t t ack e r n od e in t h e n e tw o r k . We can

m ax im ize th e numb er o f a t t a ck e r nod e and s ee th e r es u l t . Fo r t h i s

n e tw o rk s cen a r i o we us e m ax imu m 5 a t t a ck no d e .

Table 4.2 Analysis Table of Detection Rate

Ex i s t i n g At t ack e r N o d e i n

t h e N e t wo r k

D e t ec t ed At t ack e r n o de i n t h e

n e tw o rk

1 1

2 2

3 2

4 3

5 3

Figure 4.6 Detection Rate of MTV-JPDADA

F i gu r e 4 . 7 S ho w t ha t t h e f a l se n ega t ive r a t e ha s b een ca l cu l a t ed b y t h e

a l r e ad y p l aced a t t a cke r no d e m in us th e d e t ec t ed no d e b y o u r

a l go r i thm . T h i s me t r i c i s r e c i p r o ca l t o t h e d e t ec t i on r a t e . I f t h e

s im ul a t i on t i m e i s i n c r eas ed t h e Fa l s e N ega t iv e r a t e i s d ec r eas ed

b ecaus e t h e d r op co u n t o f t h e no d e i s i n c rea s i n g and i t m a y b e r each ed

o n t h e MT V , a t t h i s t im e t h e d e t ec t ion a l go r i th m can j udge t h e n od e as

a t t a ck er n od e .

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Figure 4.7 False Negative Rate of MTV-JPDADA

Fi gu r e 4 .8 s ho ws th e f a l s e p os i t i v e r a t e i s z e r o b ecau se o f M T V. A n y

i nn o cen t n od e h a s d r op p ed t he p ack e t , b u t i t do e s no t ex ceed f r om

M T V. In FJ A D A th e i nn o cen t n od e i s con s i d er ed a s m al i c i ou s .

Figure 4.8 False Positive Rate of MTV-JPDADA

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Fi gu r e 4 .9 s ho ws an En d t o En d D el a y th e p r op os ed a l go r i thm can

h i gh l y d ec r eas e d e l a y a s com p a red wi th t h e J e l l yf i s h pe r io d i c d r op

a t t a ck . So i t i s ou t s t and i n g fo r t h e n e tw o r k .

Figure 4.9 End to End Delay of MTV-JPDADA

F i gu r e 4 . 10 i nd i ca t e s t h e p ack e t d e l iv e r y r a t i o fo r J e l lyf i s h p e r i od i c

d r op a t t a ck us ed in t h i s ex p e r im en t , a f t e r d e t ec t in g t h e a t t a cks us in g

t h e p ro po s ed m e th o d . Us i n g ou r J e l l yf i s h p e r io d i c d r op a t t a ck

d e t ec t i on a l go r i thm r es u l t ed in a h igh e r p ack e t d e l i v e r y r a t i o wh en

co mp ar ed wi t h t h e J e l l yf i s h a t t a ck wi th no d e t ec t io n a l go r i t hm .

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Figure 4.10 Packet Delivery Ratio of MTV-JPDADA

A s w e can see F i gu r e 4 . 11 M TV -J P D AD A c a nn o t p ro v i d es b e t t e r

A v e r age Th ro u ghpu t w h en comp ar ed wi th J e l l yf i s h a t t a cked t h e

n e tw o rk an d t h e no r m al n e t w or k .

Figure 4.11 Average Throughput

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Chapter 5 Conclusion and Future work

5 .1 Conclusion

A Mi n im um -T h re sh o l d V a l u e Bas ed J e l l yf i s h P er io d ic D r op A t t ack

D e t ec t i on Al go r i th m ( M TV -J PD A DA ) i s p r e s en t ed f o r J e l l yf i sh

P e ro d i c D r op At t ack d e t ec t i on i n M obi l e Ad Ho c N et wo rk s w h e r e th e

b a s i c con cep t o f f r i end sh i p app roach i s ad d ed to t h e ex i s t i n g

F r i end sh i p b as ed J e l l yf i s h At t ack de t ec t io n a l go r i thm ( FJ AD A ) in

o r d e r t o k eep th e en e r g y r e s o u r ce s o f a n od e b y n o t w a t ch i n g the

ac t i v i t i e s o f i t s f r i en d n od es . Min im um -T h re sh o l d V a lu e Bas ed

J e l l yf i s h P e r i od i c D r op At t ack D et ec t io n Al go r i thm r edu ce s t h e

p os s i b i l i t y o f b l ack l i s t i n g t h e i nn o cen t n od es b y p r o v id in g a s econd

ch an ce to t h e su spec t ed no d es a f t e r ob s e rv i n g and co mpar in g t he D ro p

C ou n t wi t h t h e Min im um T h r esh o l d V a lu e (M T V ) . Th e p e r f o r man ce o f

t h e p r op os ed ap pro ach i s ev a l u a t ed i n t e rm s o f t h e At t ack D e t ec t i on

R a t e , Fa l se N ega t iv e R a t e , Fa l s e P os i t i v e R a t e , P ack e t De l i v e r y R a t io ,

A v e r age En d -T o -En d D el ay, an d N e tw o r k T hr ou gh pu t . T h e s imu l a t i o n

r e s u l t s , ev i d en t l y sh o w th a t t he p ro po s ed ap pr oach i s fu r t h e r

s t r en g th ened , and a l so s ho w i t s e f f ec t iv en ess an d d e t ec t i on e f f i c i en c y

i n t e rms o f a t t a ck d e t ec t i on r a t e , f a l se n ega t i v e r a t e , and f a l s e p os i t i v e

r a t e m et r i cs .

In t h i s t he s i s w o rk , T h e r es u l t s o f t h e ex p e r im en t s wh i ch a r e ex p l a in ed

i n t h e p r ev io us ch ap t e r . Th e f i r s t ex p e r im en t a l s cena r io i s on t he

o ccu r r en ce o f t h e a t t a ck i s t e s t ed t o ev a lu a t e t h e p e r f o rm an ce o f t he

a l r e ad y ex i s t i n g Ad ho c On Dem an d V ec to r ro u t i n g p r o t o co l wi th t he

J e l l yf i s h P er io d i c D r o p a t t a ck . Th e seco nd ex p e r i m en t a l s cen a r io t e s t s

t o ev a l u e th e p e r f o rm an ce o f J e l l yf i sh P e ro d i c Dr op A t t ack in a

s i t u a t io n w he r e t h e M in i mu m - Th re s ho ld V a l u e Bas ed J e l l yf i s h

P e r i od i c D ro p At t ack D et ec t io n Al go r i thm i s p r es en t ed fo r t h e

M A NE Ts , t o d e t e rm in e ho w th e d e t ec t i on r a t e o f M in im um T hr e sh o l d

V a lu e b as ed J e l l yf i sh p e r io d i c d ro p a t t a ck a l go r i thm w as e f f ec t iv e i n

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t h i s s i t u a t io n . F i na l l y , t h e f i nd in gs o f t h i s s t ud y g i v e w e i gh t o n t h e

i mp or t an ce an d e f f ec t iv en es s o f t h i s s t ud y, w h ich g i v e s po s i t i v e

r e s u l t s . Po s i t i v e mean s th a t t h e n e tw or k p e r fo rm an ce i n c r ea s es an d the

accu r acy l ev e l o f t h e de t ec t i on ra t e , a l so i n c r ea se w h i l e t h e t h ro u ghpu t

i s dec r eas e d s i gn i f i c an t l y. Fu r t h e r , i t i s r em ar kab l e t h a t t h e cu r r en t

f i nd i n gs ad d a n ew v i ew t o t h e s c i en ce o f d e t ec t i n g J e l lyf i s h p e r io d ic

d r op a t t a cks in t hes e s i t u a t io ns .

T h e p ro po sed app ro ach h as qu i ck l y a n d accur a t e l y , c ap ab l e t o de t ec t

t h e J e l l yf i s h p e r iod i c d ro p a t t a ck e r n od es i n t h e n e tw o r k and t he

d e t ec t i on r a t e o f t h e p ro po s ed a l go r i t hm , M ax im um 10 0 % cap ab l e i f

t h e a t t a cke r no d e i s p a r t i c ip a t in g in t h e d a t a fo r w a rd in g p r o ce ss ,

w h e r eas i f i t i s n o t i n t h e r an ge o f d a t a fo r wa r d i n g p ro ce s s t h e a t t a ck

d e t ec t i on r a t e i s dec r ea s ed r ad i ca l l y t o 60 % t h i s s cen ar io i s s am pl in g

f r om 1 0 r and om s im ul a t io n s wi th r and om m obi l i t y an d w i t h mul t ip l e

co nn ec t io n . As an av e r age t h e d e t ec t io n r a t e i s a ro u nd 8 0 . 33 %.

Fu r th e rm o re , i t a l so l imi t s t h e ab i l i t y o f t h e J e l l yf i s h p e r i od i c d rop

a t t a ck er n od es to cau s e add i t i o n a l d am age i n t h e n e t wo rk .

5 .2 Future Work

T h e Mi mim um T hre s ho ld V a lu e b as ed J e l l yf i s h P e r i od ic D ro p A t t ack

D e t ec t i on Al go r i t hm i s cons id e r ed on l y s en d i n g ro u t e e r r o r t o t h e

s ou r ce no d e an d t h e A d ho c On Dem and V ec t o r r ou t in g p r o to co l

f o l lo w s i t s d e f au l t R ou t e d i s cov e r y p r o cess and s e l ec t s t h e s ho r t e s t

p a th du r i n g t h i s t im e t h e a t t a ck e r n od e ma y b e i n t h e s e l ec t ed p a th .

U n le s s t he d e t ec t io n a l go r i t hm s en ds t h e ro u t e e r r o r m ess age t o t he

s ou r ce no d e , t h e p r o to co l s e l ec t s t h e s h or t es t p a t h f r om th e ex i s t i n g

r o u t es . A l s o , t h e A d ho c On D em and V ec t o r r ou t in g p r o to co l d id no t

ch an ge p a t h u n l e s s t h e p a th i s b r ok en o r l i n k b r eak age ex i s t s . M ak in g

t h e A d ho c O n D em and Vec to r r ou t in g p ro to co l r ou t e s e l ec t iv e , m ay

h e lp t h e d e t ec t ion a l go r i th m h ea l th i e r . Wh et h e r t h e p a t h h a s an

a t t a ck er no d e th e A d ho c On D em and V ec t o r r ou t in g p r o to co l s e l ec t s

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49

t h a t p a t h fo r t h e s econ d t im e , b u t M in imu m Th r es ho ld V a lu e b as ed

J e l l yf i s h P e r io d i c D r o p At t ack D et ec t io n Al go r i t hm cann o t av o id th i s

s ho r t comi n g . O n the o t h e r h an d , s i n ce w e h av e imp l em en t ed on e t yp e

o f J e l l yf i s h a t t a ck , w h i ch i s J e l l yf i s h P e r i od i c P ack e t D r o p At t ack s ,

t h e o t h e r t wo va r i an t s de l ay an d r eo r d e r s ho u l d b e a l so im pl em en ted

u s i n g a M in i mum T h r es ho l d V a lu e b a s ed J e l l yf i s h P e r i od i c D ro p

A t t ack D et ec t i on Al go r i thm .

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50

References

[ 1 ] S . K . S o n a l i S h a r ma , " A Re v i e w P a p e r o n S e c u r e Ro u t i n g T e c h n i q u e

f o r M A NE T s , " In t e r n a t i o n a l Re s e a r c h J o u r n a l o f E n g i n e e r i n g a n d

T e c h n o l o g y ( IRJ E T ) , v o l . 5 , n o . 6 , p p . 2 3 9 3 -2 3 9 7 , 2 0 1 8 .

[ 2 ] M . R . , N . M a n j o t K a u r 1 , " A Co mp r e h e n s i v e S t u d y o f J e l l y f i s h A t t a c k

i n M o b i l e Ad h o c Ne t wo r k s , " s e ma n t i c s c h o l a r , v o l . 3 , n o . 4 , p p . 1 9 9 -

2 0 3 , 2 0 1 4 .

[ 3 ] S . U . R . IR S H AD UL L AH , " An a l y s i s o f B l a c k H o l e a t t a c k o n M A NE T s

U s i n g d i f f e r e n t M AN E T r o u t i n g p r o t o c o l s , " d i v a -p o r t a l . o r g , 2 0 1 0 .

[ 4 ] A . V . T a r u n p r e e t Bh a t i a , " S e c u r i t y i s s u e s i n M A NE T : a s u r ve y o n

a t t a c ks a n d d e f e n s e me c h a n i s ms , " In t e r n a t i o n a l J o u r n a l o f A d v a n c e d

R e s e a r c h i n Co mp u t e r S c i e n c e a n d S o f t w a r e E n g i n e e r i n g , vo l . 3 , n o . 6 ,

p p . 1 3 8 2 -1 3 9 4 , 2 0 1 3 .

[ 5 ] P . K . S a k s h i S a c h d e v a , " De t e c t i o n a n d A n a l y s i s o f J e l l y f i s h A t t a c k i n

M AN E T s , " i e e e . o r g , 2 0 1 6 .

[ 6 ] D . S . W . A ma n d e e p K a u r , " E f f e c t s o f J e l l y F i s h A t t a c k o n M o b i l e Ad -

H o c N e t w o r k’ s R o u t i n g P r o t o c o l s , " J o u r n a l o f E n g i n e e r i n g R e s e a r c h

a n d Ap p l i c a t i o n s , vo l . 3 , n o . 5 , p p . 1 6 9 4 -1 7 0 0 , 2 0 1 3 .

[ 7 ] M . B . P r e e t y D a h i ya , " D e s i gn a n d Imp l e me n t a t i o n o f N AO DV _ E T CP t o

H a n d l e J e l l y F i s h A t t a c k , " In t e r n a t i o n a l J o u r n a l o f E n g i n e e r i n g T r e n d s

a n d T e c h n o l o g y ( I J E T T ) , v o l . 3 5 , n o . 7 , p p . 3 0 0 -3 0 4 , 2 0 1 6 .

[ 8 ] A . A . L . Bh a w n a S i n g l a , " An E v a l u a t i o n O n S e l f i s h Be h a v i o u r A t t a c k

A n d J e l l y f i s h A t t a c k s U n d e r A o d v R o u t i n g P r o t o c o l , " I n t e r n a t i o n a l

J o u r n a l I n F o u n d a t i o n s Of Co mp u t e r S c i e n c e & T e c h n o l o g y , V o l . 7 ,

N o . 2 , P p . 1 5 - 2 8 , 2 0 1 7 .

[ 9 ] A . J a i n , " P e r f o r ma n c e A n a l ys i s o f D S R Ro u t i n g P r o t o c o l W i t h a n d

Page 64: DEBRE BERHAN UNIVERSITY COLLEGE OF COMPUTING …

51

W i t h o u t t h e P r e s e n c e o f V a r i o u s A t t a c ks i n M A NE T , " In t e r n a t i o n a l

J o u r n a l o f E n g i n e e r i n g Re s e a r c h a n d G e n e r a l S c i e n c e , v o l . 4 , n o . 1 ,

p p . 4 5 4 -4 6 1 , 2 0 1 6 .

[ 1 0 ] A . N . P . J a ys h r e e G o j i ya , " An E n h a n c e d A p p r o a c h o f D e t e c t i o n a n d

P r e ve n t i o n o f B l a c k H o l e A t t a c k o n A O DV o v e r M A N E T , "

In t e r n a t i o n a l J o u r n a l o f Co mp u t e r Ap p l i c a t i o n s , v o l . 1 4 2 , n o . 1 3 , p p .

9 -1 1 , 2 0 1 6 .

[ 1 1 ] A . S . A . M . V , " D i r e c t T r u s t -Ba s e d De t e c t i o n An d Re c o v e r y P r o c e s s

O f J e l l y f i s h A t t a c k In M a n e t , " I n t e r n a t i o n a l J o u r n a l Of E me r g i n g

T e c h n o l o g y In Co mp u t e r S c i e n c e & E l e c t r o n i c s , V o l . 2 2 , No . 2 , P p .

3 2 -3 8 , 2 0 1 6 .

[ 1 2 ] L a x mi , V i j a y , e t a l . " J e l l y f i s h a t t a c k : A n a l y s i s , d e t e c t i o n , a n d

c o u n t e r me a s u r e i n T C P -b a s e d M AN E T . " J o u r n a l o f In f o r ma t i o n

S e c u r i t y a n d Ap p l i c a t i o n s 2 2 ( 2 0 1 5 ) : 9 9 -1 1 2 .

[ 1 3 ] P . M . M . , P . M . B . P a t e l P o o j a B . , " J e l l y f i s h A t t a c k D e t e c t i o n a n d

P r e ve n t i o n i n M A NE T , " In t e r n a t i o n a l C o n f e r e n c e o n S e n s i n g , S i g n a l

P r o c e s s i n g a n d S e c u r i t y ( IC S S S ) , p p . 5 4 -6 0 , 2 0 1 7 .

[ 1 4 ] K . D . , A . G . S u n i l K u ma r , " F J AD A: F r i e n d s h i p Ba s e d J e l l y f i s h A t t a c k

D e t e c t i o n A l g o r i t h m f o r M o b i l e A d Ho c N e t wo r ks , " S p r i n g e r

S c i e n c e + B u s i n e s s M e d i a , L L C , p a r t o f S p r i n ge r N a t u r e , 2 0 1 8 .

[ 1 5 ] X . J . L . a . P . H . J . C . R u o J u n C a i , " An E v o l u t i o n a r y S e l f - C o o p e r a t i v e

T r u s t S c h e me A ga i n s t R o u t i n g D i s r u p t i o n s i n M A N E T s , " IE E E

T r a n s a c t i o n s o n M o b i l e C o mp u t i n g , p p . 2 -1 4 , 2 0 1 8 .

[ 1 6 ] T h o r a t , S a n d e e p A . , a n d P . J . K u l ka r n i . " D e s i g n i s s u e s i n t r u s t -b a s e d

r o u t i n g f o r M A NE T . " F i f t h In t e r n a t i o n a l Co n f e r e n c e o n Co mp u t i n g ,

C o mmu n i c a t i o n s a n d Ne t wo r k i n g T e c h n o l o g i e s ( IC C C NT ) . IE E E , 2 0 1 4 .

[ 1 7 ] S a ma d , F . ( 2 0 1 1 ) . S e c u r i n g w i r e l e s s me s h n e t wo r k s : a t h r e e -

Page 65: DEBRE BERHAN UNIVERSITY COLLEGE OF COMPUTING …

52

d i me n s i o n a l p e r s p e c t i ve . Do c t o r a l d i s s e r t a t i o n . RW T H Aa c h e n

U n i v e r s i t y , Ge r ma n y .

[ 1 8 ] G u i za n i , M . , R a ye s , A . , K h a n , B . & Al -F u q a h a , A . 2 0 1 0 . Ne t w o r k

M o d e l i n g An d S i mu l a t i o n : A P r a c t i c a l P e r s p e c t i ve , J o h n W i l e y &

S o n s .

[ 1 9 ] Q u i n t e r o , R . M . H . , G a r c i a , J . A . G . , T o r c a t t , C . M . & H e r n a n d e z , F .

2 0 1 3 . Ne t wo r k S i mu l a t o r -N s 2 . Re v i s t a De T e c n o l o g i a E In f o r ma c i o n ,

1 .

[ 2 0 ] I s s a r i ya k u l , T . & Ho s s a i n , E . 2 0 1 1 . In t r o d u c t i o n T o Ne t wo r k S i mu l a t o r

N s 2 , S p r i n g e r S c i e n c e & Bu s i n e s s M e d i a

[ 2 1 ] S h i , S . , Gu , X . -M . , Z h a n g , W . -B . & S h a , X . - J . 2 0 0 8 . W o r k i n g

M e c h a n i s m A n d Co d e A n a l ys i s Of Ns 2 S i mu l a t i o n F o r M o b i l e A d Ho c

N e t wo r ks [ J ] . Co mp u t e r E n g i n e e r i n g An d D e s i gn , 1 8 , 0 0 2 .

[ 2 2 ] P a r s o n s , M a l c o l m, a n d P e t e r E b i n ge r . " P e r f o r ma n c e e va l u a t i o n o f t h e

i mp a c t o f a t t a c k s o n mo b i l e a d h o c n e t wo r k s . " p r o c e e d i n gs o f F i e l d

F a i l u r e Da t a An a l y s i s W o r k s h o p S e p t e mb e r 2 7 -3 0 , N i a ga r a F a l l s , Ne w

Y o r k , US A . 2 0 0 9 .

[ 2 3 ] R o y , De b d u t t a Ba r ma n , R i t u p a r n a C h a k i , a n d N a b e n d u C h a k i . " A n e w

c l u s t e r -b a s e d w o r mh o l e i n t r u s i o n d e t e c t i o n a l g o r i t h m f o r mo b i l e a d -

h o c n e t w o r ks . " a r X i v p r e p r i n t a r X i v : 1 0 0 4 . 0 5 8 7 ( 2 0 1 0 ) .

[ 2 4 ] A g g a r wa l , N i t i n , a n d K a n t a D h a n k h a r . " A t t a c k s o n M o b i l e Ad h o c

N e t wo r ks : A S u r ve y . " In t e r n a t i o n a l J o u r n a l o f Re s e a r c h i n A d v e n t

T e c h n o l o g y 2 . 5 ( 2 0 1 4 ) : 3 0 7 -3 1 6 .

[ 2 5 ] V e t t e r l i , M a r t i n , J e l e n a K o v a č e v i ć , a n d V i ve k K . G o ya l . F o u n d a t i o n s

o f s i g n a l p r o c e s s i n g . Ca mb r i d ge U n i ve r s i t y P r e s s , 2 0 1 4 .

[ 2 6 ] An k i t M . V a g h e l a , P r o f . A s h i s h P a t e l “ M i t i ga t i o n a n d D e t e c t i o n o f

Page 66: DEBRE BERHAN UNIVERSITY COLLEGE OF COMPUTING …

53

J e l l y f i s h De l a y V a r i a n c e A t t a c k i n M ANE T ” IJ S A RT , 2 0 1 7 Vo l u me 3

I s s u e 1 1

[ 2 7 ] M a n ve e n K a u r 1 * , J a s h a n p r e e t K a u r “ Id e n t i f i c a t i o n a n d Re mo v a l o f

J e l l y -F i s h A t t a c k i n Io T ” I n t e r n a t i o n a l J o u r n a l o f Co mp u t e r S c i e n c e s

a n d E n g i n e e r i n g V o l . -6 , I s s u e -5 , J u n 2 0 1 8

[ 2 8 ] A l s u ma y t , A l b a n d a r i . M i t i ga t e d e n i a l o f s e r v i c e a t t a c k s i n mo b i l e a d -

h o c n e t w o r ks . D i s s . N o t t i n g h a m T r e n t Un i v e r s i t y , 2 0 1 7 .

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54

Appendix

Implementing Jellyfish Periodic Drop Attack in AODV

/ / = = = = = = = In a o d v . h p u t t h e f o l l o wi n g l i n e i n A O DV Cl a s s

b o o l a t t a c ke r ;

i n t d r o p _ c o u n t ;

M a c * ma c _ ;

/ / i n t d _ c o u n t [ 1 0 0 0 ] ;

/ / = = = = = In a o d v . c c p u t t h e f o l l o wi n g l i n e i n i n t AO DV : : c o mma n d

I f ( s t r c mp ( a r g v [ 1 ] , " j f " ) = = 0 ) {

a t t a c ke r = t r u e ;

r e t u r n T C L _ OK ;

}

/ / = = = = i n a o d v . c c p u t t h e f o l l o wi n g l i n e i n A O DV : : A O DV ( n s a d d r _ t i d ) :

a t t a c ke r = f a l s e ;

r c o u n t = 0 ;

f c o u n t = 0 ;

d r o p _ c o u n t = 0 ;

/ / = = = = = i n a o d v . c c p u t t h e f o l l o wi n g l i n e i n v o i d A O DV : : f o r w a r d

i n t x ;

x = Ra n d o m: : u n i f o r m( 0 , 1 0 0 ) ;

e l s e {

/ / No t a b r o a d c a s t p a c k e t , n o d e l a y , s e n d i mme d i a t e l y

i f ( a t t a c ke r = = t r u e ) {

p r i n t f ( " A t t a c k i s T r u e a n d p a c ke t t yp e i s n o t T C P \n " ) ;

i f ( c h -> p t yp e _ = = P T _ T CP o r c h -> p t yp e _ = = P T _ CB R o r c h -> p t yp e _

= = P T _ ACK ) {

Page 68: DEBRE BERHAN UNIVERSITY COLLEGE OF COMPUTING …

55

i f ( x > 9 0 ) {

p r i n t f ( " A t t a c k i s T r u e a n d Ra n d o m x i s = % d \n " , x ) ;

d r o p _ c o u n t + + ;

p r i n t f ( " P a c k e t d r o p p i n g n o d e % d i s d r o p p e d % d P a c ke t s \ n " , i n d e x ,

d r o p _ c o u n t ) ;

d r o p ( p , D RO P _ RT R_ R O UT E _ L OO P ) ;

/ / r e t u r n ;

} e l s e {

S c h e d u l e r : : i n s t a n c e ( ) . s c h e d u l e ( t a r g e t _ , p , 0 . ) ;

}

} e l s e {

S c h e d u l e r : : i n s t a n c e ( ) . s c h e d u l e ( t a r g e t _ , p , 0 . ) ;

i f ( i n d e x = = 0 ) {

i f ( c h -> p t yp e _ = = P T _ T CP ) {

f c o u n t + + ;

}

}

}

} e l s e {

S c h e d u l e r : : i n s t a n c e ( ) . s c h e d u l e ( t a r ge t _ , p , 0 . ) ;

}

}

}