1. BNM INSTITUTE OF TECHNOLOGY
Technical seminar on
A Mutual Trust Based Access Control in Cloud
Computing
Presented by,
Sanju A.N.
Mtech CSE
Under the guidance of,
Mr. Prashanth J
Assistant Professor
Dept. of CSE, BNMIT

2. 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.
MTBAC 1

3. 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..

4. MTBAC 4
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.

5. MTBAC 5
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.

6. MTBAC 6
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.

7. The division of trust attributes
MTBAC 7
Fig.1 The division of trust attributes

8. MTBAC 8
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).

9. MTBAC 9
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

10. MTBAC 10
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}.

11. MTBAC 11
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:

12. MTBAC 12
 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…..

13. MTBAC 13
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……

14. MTBAC 14
Continued…..
g) Mutual Trust Threshold
Mutual Trust Threshold MTT is composed of a binary group,
h) Trust Decision
Trust decision can be formulized as ,

15. MTBAC 15
Continued…..
2. Mutual trust mechanism
 Bidirectional trust structure.
 Collection and processing of behavior trust information.
 Computing and updating of trust values.

16. MTBAC 16
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

17. MTBAC 17
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.

18. 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.
MTBAC 18

19. MTBAC 19
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

20. COP 5614 - Operating Systems 20
Continued…..
2. Comparison experiment of different mutual trust thresholds

21. MTBAC 21
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.

22. MTBAC 22
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=6
827577&queryText%3Dmtbac.

23. MTBAC 23