BNM INSTITUTE OF TECHNOLOGY

Technical seminar onA Mutual Trust Based Access Control in Cloud

ComputingPresented by,Sanju A.N.Mtech CSE

Under the guidance of,Mr. Prashanth J Assistant Professor Dept. of CSE, BNMIT

MTBAC

CONTENTS

1. Introduction.

2. Literature Survey.

3. Mutual Trust Between Cloud User And Cloud

Service Node.

4. Mutual Trust Based Access Control Model In

Cloud Computing Environment, MTBAC.

5. MTBAC Simulation and Experiment.

1

MTBAC 2

INTRODUCTION

Cloud computing is a service delivering mode based on the

Internet.

Cloud computing environment is a typical distributed environment.

Access control is one of the most important measures to ensure the

security of cloud computing..

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LITERATURE SURVEY

In 1994, Marsh put forward the concept of trust for the first time, and then

Baize introduced trust management into network security applications.

Hassan proposed a novel trust evaluation method suitable for the pervasive

environment.

According to algebraic theory of semi-rings, George presented a new trust

modeling method, which defined trust relationship as a directed graph path

problem.

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Continued…

Wang Wej built a trust model based on Bayesian theory and proposed a

trusted resource scheduling algorithm.

Jong P. Yoon et al proposed a credible model for cloud resources based

on authorization chain.

Santos et al proposed a trusted cloud computing platform (TCCP) on

which IaaS service providers could offer a closed box-type execution

environment.

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Mutual Trust Between Cloud User And Cloud Service Node

The mutual trust mechanism of users and cloud service nodes has a two-

part structure.

i. Users' behavior trust model

a) Acquisition of user's behavior information.

b) The division of trust attributes.

c) Quantitative expression of user behavior trust.

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The division of trust attributes

Fig.1 The division of trust attributes

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Continued…..

ii. Trust model of cloud service nodes.

The behavior trust mechanism of cloud service nodes is based on

Ant colony algorithm.

a) Trust Degree

The tendency which entity the user would choose to interact. At time t,

trust degree of cloud service node c is expressed as Tc (t) E [0,1].

b) Direct trust

Direct trust relationship is built through direct experience of

interactions between the user and entity, formulized as Dtc (t).

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Continued…..

c) Trust pheromone

A primary cognition of direct trust degree between the user and the

entity. At time t, user U's trust pheromone towards cloud service

node c is formulized by Tpc (t).

d) Heuristic pheromone

User's cognitive information about the service node. User's

cognitive information is the Euler distance between the user and

the entity, formulized as

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Continued…..

In cloud computing, user's choice of cloud service nodes is

expressed by direct trust degree.

Where α is the weight of trust pheromone between user u and e, β

is the weight of heuristic pheromone. E is a set of user-selectable

cloud service nodes. Here E = {1, 2,…, m}.

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Continued…..

e) Recommend trust Recommend trust is recommended by some intermediate entity.

formulized as

Different intermediate entities have different significance on

trust

values.

Intermediate entity k belongs to N = {1, 2,··· , n}. At time t,

user

U's recommended trust towards cloud service node C is

expressed as follows:

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Trust between a user and a node consists of two parts, direct trust δ1

and recommended trust δ2.

Trust pheromone between entities will be gradually reduced over time,

therefore, we need to make updates of trust pheromone timely.

Where, is the decay factor of trust pheromone represents the

increment of trust pheromone in the time period of (t,t + 1).

Continued…..

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According to deterministic theory, the following formula defines transitive

relations of trust between the user and the entity.

iii. Mutual Trust between users and cloud service nodes

1. Mutual Trust definition

f) Mutual trust

The confidence that both users and cloud service nodes have

shown to each other in the face of uncertainty in future

interactions.

Continued……

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Continued…..

g) Mutual Trust ThresholdMutual Trust Threshold MTT is composed of a binary group,

h) Trust DecisionTrust decision can be formulized as ,

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Continued…..

2. Mutual trust mechanism

Bidirectional trust structure.

Collection and processing of behavior trust information.

Computing and updating of trust values.

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Mutual Trust Based Access Control Model In Cloud Computing Environment, MTBAC

1. The structure of MTBAC

The physical structure of MTBAC

consists of users, authentication and

authorization center (AAC), cloud

service nodes, user's behavior trust

database and cloud service node's

trust database

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MTBAC

2. Algorithm of MTBAC

1. AAC checks whether user has valid authentication token.

2. Compare the user's trust level with the trust threshold, if it is higher

than the threshold, turn to step (3); else, refuse to provide services

to the user.

3. Read the user's access request, and put all the cloud nodes which

could provide the corresponding service into the candidate node

queue.

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Continued…..

4. Select the best service node in the candidate node queue and give the

user the service access right

5. Updates user's trust degree.

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MTBAC SIMULATION AND EXPERIMENT

Based on the rate of successful transaction (RST) as performance

measurement. RST is the proportion of successful interact times in all

interactions between users and cloud service nodes.

1. The comparison among CSTBAC, UTBAC and MTBAC

COP 5614 - Operating Systems 20

Continued…..

2. Comparison experiment of different mutual trust thresholds

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CONCLUSIONS

MTBAC take both user's behavior trust and cloud service node's trust

into consideration.

MTBAC adapts to the characteristics of uncertainty, dynamism and

distribution in cloud computing.

User's behavior is divided into three types in user's trust model and each

type of attribute has a certain weight.

User' s trust level will be acquired through trust quantization of user's

behavior.

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References

I. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?

arnumber=485845

II. https://hal.inria.fr/file/index/docid/695951/filename/article1-10-

HAL-1.pdf

III. Guoyuan Lin, Shan He, Hao Huang. Access Control Security

Model Based on Behavior in Cloud Computing Environment[J].

Journal of China Institute of Communications, 2012, 33(3).

IV. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?

tp=&arnumber=6827577&queryText%3Dmtbac.

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Thank you