1. 1 Objective and Secure Reputation-Based Incentive Scheme for Ad-Hoc Networks Dapeng Oliver Wu Electrical and Computer Engineering University of Florida (Joint work with Qi He and Pradeep Khosla at Carnegie Mellon University)

2. 2 What’s the Problem? Mobile ad hoc network (MANET) has no fixed infrastructure Communications rely on intermediate nodes But why should intermediate nodes relay? Need incentive mechanism for packet forwarding in non-cooperative MANET

3. 3 Outline Problem and motivation Previous work  Reputation-based schemes  Pricing-based schemes Our scheme  Design objective  Basic scheme  Security enhancement Conclusion

4. 4  Watchdog: identifies selfish nodes Mitigating Routing Misbehavior (S. Marti et al, Stanford University, 2000) S A B C D X S A B C D X Y  Pathrater: gets around identified selfish nodes

5. 5 Pros and Cons Pros:  Improve throughput Cons:  Unfairly makes well behaving nodes busier  Indirectly encourages misbehavior (S. Marti et al, Stanford University, 2000)

6. 6  Detect misbehavior of neighbors  Share reputation information with friends  Punish selfish nodes based on the shared information CONFIDANT Protocol System (S. Buchegger and J-Y Le Boudec, IBM and EPFL, 2002)

7. 7 Pros and Cons Pros  Use keys to authenticate nodes  Identify and punish misbehavior Cons  How to build a network of friends is not clear  Key distribution is not addressed  Globally shared reputation makes it not scalable (S. Buchegger and J-Y Le Boudec, IBM and EPFL, 2002)

8. 8 Where are we? Problem and motivation Previous work  Reputation-based schemes  Pricing-based schemes Our scheme  Design objective  Basic scheme  Security enhancement Conclusion

9. 9 Enforcing Service Availability Scheme  Virtual currency (nuglet)  Centralized authority issuing nuglets  Same amount of packets to forward  Tamper-resistant hardware Problem:  Require balanced traffic (L. Buttyan and Hubaux, Swiss Federal Institute of Technology -- EPFL, 2000)

10. 10 Micro-payment Scheme Encouraging Collaboration Multi-hop Cellular Networks (hybrid network)  Mobile nodes form ad-hoc networks  Base stations are connected to a backbone network M. Jakobsson, J-P Hubaux, and L. Buttyan RSA Lab, Swiss Federal Institute of Technology, 2003 backbone

11. 11 $ Micro-payment Protocol 1.Select a reward Forward the packet Keep the MAC for reward 1.Check MAC 2.Send service record to clearing house Accounting Center (Clearing house) backbone M. Jakobsson, J-P Hubaux, and L. Buttyan RSA Lab, Swiss Federal Institute of Technology, 2003 Registers to home network which shares a secret key move MAC 2.Generate an MAC 3.Send out the packet

12. 12 Pros and Cons Pros  Symmetric key crypto: reduce computational cost  Payment aggregation: lower communication cost Cons  Substantial communication overhead  Requirement of infrastructure  Centralized trust authority M. Jakobsson, J-P Hubaux, and L. Buttyan, RSA Lab, Swiss Federal Institute of Technology 2003

13. 13 Where are we? Problem and Motivation Previous work  Reputation-based schemes  Pricing-based schemes Our scheme  Design objective  Basic scheme  Security enhancement Conclusion

14. 14 Our Design Objectives  Practicality  Available technologies  Realistic context of ad-hoc networks  Efficiency  Affordable computational cost  Moderate communication overhead

15. 15 Assumptions  Nodes are non-cooperative  No collusion among nodes  Broadcast transmission  All participating nodes desire to communicate  Invariant identity  Selfish but not malicious  Promiscuous mode (listening mode)

16. 16 Where are we? Problem and motivation Previous work  Reputation-based schemes  Pricing-based schemes Our scheme  Design objectives  Basic scheme  Security enhancement Conclusion

17. 17 Neighbor Monitoring  Each node N maintains a Neighbor Node List (NNL N )  RFP N (X): (Requested to Forward Packets) The number of packets N requests X to forward  HFP N (X): (Has Forwarded Packets) The number of packets that have been forwarded by X and noticed by N  LER N (X): Local Evaluation Record {G N (X), C N (X)} Generosity Confidence

18. 18 Reputation Propagation  Every neighbor has its local evaluation record about X. node i earned from N.  Everyone periodically broadcasts its LER(X). G B (X), C B (X)  Compute Overall Evaluation Record OERN(X) X N A B C A (X), G A (X) C B (X), G B (X) C N (X), G N (X) C A (X), G A (X) ****** ****** if RFP N (X)  0 otherwise Credibility  Everyone periodically broadcasts its LER(X).  Compute Overall Evaluation Record OERN(X) if RFP N (X)  0 otherwise Credibility

19. 19 Remarks  Quantified by objective observations  Weighted by confidence for accuracy  Weighted by credibility to limit impact of selfish nodes e.g., fake a non-existing node to broadcast information

20. 20 Punishment Action if otherwise Drop packets from X with a probability p : Selfishness q = 1 - OER N (X)

21. 21 Simulation Setup  Network Simulator (NS-2)  Total number of nodes: 50 (5 selfish nodes)  Area: 670X670m 2  IEEE 802.11 for medium access control  DSR for routing  CBR traffic: 1 packet/s  No. of connections: 10  Connection duration: 10s  Random waypoint mobility model  Max speed of movement: 20m/s

22. 22 Simulation Results

23. 23 Where are we? Problem and motivation Previous work  Reputation-based schemes  Pricing-based schemes Our scheme  Design objectives  Basic scheme  Security enhancement Conclusion

24. 24 Potential Vulnerability Impersonate a node with a good reputation to propagate fake observation information X N A B C A (X), G A (X) C B (X), G B (X) C A (X), G A (X)

25. 25 Identification and Authentication … … … ID … … … f ff f f Computationally infeasible to impersonate other nodes without knowing their keys

26. 26 Conclusion  Incentive scheme with punishment mechanism Reputation objectively quantified by observations Punishment action quantitatively suggested by reputation Effectively identify and punish selfish nodes  Security enhancement Identification and authentication constructed collectively Protection from impersonation

27. 27 Thank you!