an authentication service against dishonest users in mobile ad hoc networks

An Authentication Service Against Dishonest Users in Mobile Ad Hoc Networks

Edith Ngai, Michael R. Lyu, and Roland T. Chin

IEEE Aerospace Conference, Big Sky, MT, March 6-13, 2004

Dept. of Computer Science & Engineering, CUHK

2

Outline

IntroductionRelated WorkModelsSecurity OperationsSimulation ResultsConclusion


3

Mobile Ad Hoc Networks

Infrastructure-lessMulti-hopsWireless communicationsHighly mobileDynamic topologyVulnerable to security attacks


4

Introduction

Certificate-based approachFully distributed mannerDetect false public key certificatesIsolate dishonest usersPropose a secure, scalable and distributed

authentication serviceAssure correctness of public key

certification


5

Related Work

Traditional network authentication solutions rely on physically present, trust third-party servers, or called certificate authorities (CAs).

Partially-distributed certificate authority makes use of a (k,n) threshold scheme to distribute the services of the certificate authority to a set of specialized server nodes.

Fully-distributed certificate authority extends the idea of the partially-distributed approach by distributing the certificate services to every node.


6

Related Work

Pretty Good Privacy (PGP) is proposed by following a web-of-trust authentication model. PGP uses digital signatures as its form of introduction. When any user signs for another user's key, he or she becomes an introducer of that key. As this process goes on, a web of trust is established.

Self-issued certificates issue certificates by users themselves without the involvement of any certificate authority.


7

Our Work

Propose a secure public key authentication service in mobile ad hoc networks with malicious nodes

Prevent nodes from obtaining false public keys of the others

Based on a network model and a trust model Security operations include public key certification and

trust value update


8

Architecture

•Clustering-based network model

•Trust model with an authentication metric

•Security operations to detect and isolate malicious nodes


9

The Network Model

Obtain a hierarchical organization Minimize the amount of storage for

communication information Optimize the use of network bandwidth Direct monitoring capability is limited to

neighboring nodes Allow the monitoring work to proceed more

naturally Improve network security


10

The Network Model

Divide the network into different regions

Each region with similar number of nodes

Unique group ID E.g. Zonal distributed

algorithm, Weight base clustering algorithm, etc

Group 1

Group 2

Group 3

Group 4

Group 5


11

The Trust Model

Define a fully-distributed trust management algorithm that is based on the web-of-trust model, in which any user can act as a certifying authority

This model uses digital signatures as its form of introduction. Any node signs another's public key with its own private key to establish a web of trust

Our trust model does not have any trust root certificate; it just relies on direct trust and groups of introducers in certification


12

The Trust Model

Define the authentication metric as a continuous value between 0.0 and 1.0

A direct trust is the trust relationship between two nodes in the same group

A recommendation trust is the trust relationship between nodes of different groups

s

Group 1

Group 2

Group 3

Group 4

Group 5

Direct Trust

RecommendationTrust


13

Security Operations

Select introducers Send request messages Compare certificates

received Trust value update

Discovers maliciousintroducer?

Selects a number of trustablenodes as introducers

Sends out request messages tointroducers

Collects and compares all thepublic key certificates received

Selects the public key of tfollowing the majority votes

Calculates trust value of t

Updates trust table

Isolates maliciousintroducer

Y

N


14

Authentication in our network relies on the public key certificates signed by some trustable nodes.

Nodes in the same group are assumed to know each other by means of their monitoring components and the short distances among them

Public Key Certification

s

i1

t

i2

in

Group 1

Group 2

Group 3

Group 4

Group 5

…...

Reply

Request


15

Operation of Node

Select introducers Send request messages

to introducers Collect and decrypt the

messages Compare the certificates,

isolate dishonest nodes Calculate trust value of

the new node


16

Trust Value Update

s denotes the requesting node

t denotes the target node Nodes i1, i2, …, in are the

introducers Each Vs, i* and Vi*, t form a

pair to make up a single trust path from s to t

s

i2

i1

t

in

…...

RecommendationTrust

Direct Trust

Vs,i1

Vs,i2

Vs,in

Vi1,t

Vi2,t

Vin,t


17

Trust Value Update

Compute the new trust relationship from s to t of a single path

Combine trust values of different paths to give the ultimate trust value of t

Insert trust value Vt to the trust table of s

1221 )1(1 VVVV

,

1 1

1 (1 )i

i

m n

ncom i j

i j

V V


18

Simulation Set-Up

Network simulator Glomosim

Evaluate the effectiveness in providing secure public key authentication in the presence of malicious nodes

Simulation Parameters


19

Metrics

Successful rate % of public key requests that lead to a correct

conclusion

Failure rate % of public key requests that lead to an incorrect

conclusion

Unreachable rate % of public key requests that cannot be made due to not

enough number of introducers


20

Ratings to Periods of Time

Ratings to Time with m=70% and p=40%

0

10

20

30

40

50

60

70

80

90

100

0-1000 1000-2000 2000-3000 3000-4000

Number of Requests

Rat

ings

(%) Successful rate

Failure rateUnreachable rate


21

Ratings to Malicious Nodes

Ratings to % of Malicious Nodes with p=30%

0

10

20

30

4050

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100

% of Malicious Nodes

Rat

ings

(%)

Successful rate

Failure rate

Unreachable rate

Ratings to % of Malicious Nodes with p=60%

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100

% of Malicious NodesR

atin

gs (%

)

Successful rate

Failure rate

Unreachable rate


22

Ratings to Trustable Nodes at Initialization

Ratings to % of Trustable Nodes at Initialization with m=30%

0

10

20

30

40

50

60

7080

90

100

0 10 20 30 40 50 60 70 80 90 100

% of Trustable Nodes at Initialization (p)

Rat

ings

(%)

Successful rate

Failure rate

Unreachable rate

Ratings to % of Trustable Nodes at Initialization with m=70%

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100

% of Trustable Nodes at Initialization (p)R

atin

gs (%

)

Successful rate

Failure rate

Unreachable rate


23

Comparison with PGP- Successful Rate

Successful Rate to % of Malicious Nodes

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100


Succ

essf

ul R

ate

(%)

Authentication serviceproposed

Pretty good privacy


24

Comparison with PGP - Failure Rate

Failure Rate to % of Malicious Nodes

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100


Failu

re R

ate

(%)

Authentication serviceproposedPretty good privacy


25

Comparison with PGP - Unreachable Rate

Unreachable Rate to % of Malicious Nodes

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100


Unr

each

able

Rat

e (%

) Authentication serviceproposedPretty good privacy


26

Conclusions

We developed a trust- and clustering-based public key authentication mechanism

We defined a trust model that allows nodes to monitor and rate each other with quantitative trust values

We defined the network model as clustering-based The authentication protocol proposed involves new security

operations on public key certification, update of trust table, discovery and isolation on malicious nodes

We conducted security evaluation We compared with the PGP approach to demonstrate the

effectiveness of our scheme

an authentication service against dishonest users in mobile ad hoc networks

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