1. 1 Service Sharing with Trust in Pervasive Environment: Now it’s Time to Break the Jinx Sheikh I. Ahamed, Munirul M. Haque and Nilothpal Talukder Ubicomp Research Lab Ubicomp Research Lab(www.mscs.mu.edu/~ubicomp) Department of Mathematics, Statistics and Computer Science Marquette University, Milwaukee, Wisconsin

2. 2 Outline Introduction and background Motivation Trust model Evaluation Conclusion Future work

3. 3 –The number of handheld users will reach 2.6 billion this year and 4 billion by 2010 portable low-cost lightweight devices and emergent short range, and low power wireless communication networks –In USA, seniors over age 65 whose numbers are expected to hit 70 million by 2030, almost doubling from 35 million in 2000 Introduction and background

4. 4 Pervasive Computing What it means – Pervasive computing is the computation that’s freely available everywhere Goals of it – Integrate computing and communications with the surrounding physical environment – Make computing and communication transparent to the users

5. 5 Pervasive Computing Environment (a)Ad hoc network in pervasive environment with powerful device support (b) Ad hoc network in pervasive environment without powerful device support

6. 6 Motivation for trust model Depend on each other for resources –Poor battery power –Small memory storage –Poor computational capability Susceptible and vulnerable to malicious snoopers –Inter-device dependency –Common shared medium –Transitory connectivity –Absence of a fixed trust infrastructure

7. 7 Motivation for trust model : cont. With which node(s) should I interact and with which I do not? –Trust models Responsible for establishing and managing trust relationships Decision-making role in resource sharing Request from unknown device –Decision based on recommendation –Identify malicious recommendation

8. 8 Features of a Trust Model F1. Only valid nodes should be able to take part in any interaction F2. Only authorized nodes should get a requested service F3. A valid node may not be remained valid forever

9. Why Trust in Access Control Framework Consider a scenario in which node A wants to share or to get access to node B’s resources. The first thing B will do is to reason about the trustworthiness of A. B will accomplish this by analyzing accumulated data from the previous interactions or requesting some recommendations from his trusted parties in the case that A has not had any interactions with B before. There may also be a situation where there might not be enough information to trust, then B has to make his decision based on other variables [1]. 9

10. Why Trust in Access Control Framework (cont.) Because B cannot also allow access to his resources for an indefinite amount of time, his access policies will be dynamically updated on the information based on trust over time. The service delivery agent running on B will consult the access control to decide on access. If trust values are satisfactory A is immediately provided access. The interaction will also be used to modify the existing trust status of A. 10

11. 11 Trust Framework Two units –Direct Trust Unit Formed through direct interaction experience Behavior model –Evaluate the satisfaction level –Recommended Trust Unit Recommended trust Protocol –Evaluate the recommendations

12. 12 Recommended Trust Active Recommendation –Active recommendation is possible only from neighboring nodes, Passive –the node might consider all path that has hop length >=2. Discrete –When a node can’t reach any path to consider it for recommendation, it needs some way to resolve the issue. That’s what we term discrete recommendation.

13. 13 Hop Based Recommendation Protocol (HBRP) a hop based recommendation protocol to determine trust values to consider a node eligible for access. this protocol actually includes mechanisms for active and passive recommendations. the maximum path length enables a node to avoid a long chain of recommendations. This value is reduced in each hop by 1 and the path is ignored when the field becomes 0.

14. 14 Risk in trust: handling malicious recommendation Sometimes a node is in a scenario where the recommendation value contrasts the current recommendation value. It is a malicious recommendation. There can be two such situations. –a) When a malicious node gives a high recommendation value for a node when the overall value is poor. – b) When a malicious node recommends a very low value contrasting high recommendations from others. We have adopted a statistical method (t-Estimate) to address this issue of malicious recommendation. Our assumption is that the number of benevolent nodes is much larger compared to the number of malicious nodes.

15. 15 Evaluation Implementation of the prototype –Operating system: WINCE –PDA: Axim X50vProcessor –Programming language: VC#.Net Compact Framework –Mobile ad-hoc mode: IEEE 802.11b FTM

16. Screenshots of the Service sharing application based on trust based access control 16

17. Usability Survey 17

18. 18 Conclusion We presented a trust model to fit the dynamic access control framework intended for pervasive environment. We used this information to optimize the accuracy of the recommendation process and the discarding of malicious devices from the network. The prototype of the secured service sharing application presented in the evaluation section uses this hop-based recommendation protocol. We have incorporated the risks involved in the different sharing scenarios

19. 19 Future work As a continuous addendum to the features, this access control module will be placed in the MARKS (Middleware Adaptability for resource Discovery, Knowledge Usability, and Self Healing) middleware. Apart from security issues in service sharing, our future research lies with privacy issues that may arise due to context-awareness of applications in the pervasive environment

20. 20 Questions Send questions to –iq@mscs.mu.edu