1 / 36

Denial of Service Resilience in Ad Hoc Networks

Denial of Service Resilience in Ad Hoc Networks. Imad Aad, Jean-Pierre Hubaux, and Edward W. Knightly. Designed by Yao Zhao. Motivation. Do ad hoc networks have sufficiently redundant paths and counter-DoS mechanisms to make DoS attacks largely ineffective?

pepin
Télécharger la présentation

Denial of Service Resilience in Ad Hoc Networks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Denial of Service Resilience in Ad Hoc Networks Imad Aad, Jean-Pierre Hubaux, and Edward W. Knightly Designed by Yao Zhao

  2. Motivation • Do ad hoc networks have sufficiently redundant paths and counter-DoS mechanisms to make DoS attacks largely ineffective? • Or are there attack and system factors that can lead to devastating effects?

  3. Outline • Introduction and system model • DoS attacks • Analytical model • Evaluation • Related works • Conclusion

  4. Introduction to Ad hoc networks

  5. System Model (1) • Ensure node authentication • Ensure message authentication • Ensure one identity per node • Prevent control plane misbehavior (query floods, rushing attacks)

  6. System Model (2)

  7. Outline • Introduction and system model • DoS attacks • JellyFish • Black holes • Analytical model • Evaluation • Related works • Conclusion

  8. JellyFish Attack • Protocol Compliance • Protocols with congestion control such as TCP • Just like any IP service, it can: • Drop packets, Reorder packets, Delay / jitter packets • But • in a MALICIOUS way • Detection and diagnosis are time consuming! • Three attack ways • JF Reorder Attack • JF Periodic Dropping Attack • JF Delay Variance Attack

  9. JF Reorder Attack • Facts • TCP’s use of cumulative acknowledgements • All such TCP variants assume that reordering events are rare • Attack strategy • deliver all packets, yet after placing them in a re-ordering buffer rather than a FIFO buffer.

  10. Attack strategy

  11. Impact of JF Reorder Attack

  12. JF Periodic Dropping Attack • Facts • If losses occur periodically near the retransmission time out (RTO) timescale (in the 1s range as RTO is intended to address severe congestion), then end-to-end throughput is nearly zero • Endpoint attack • Attack strategy • Periodic dropping attack in which attacking nodes drop all packets for a short duration (e.g., tens of ms) once per RTO • Passive

  13. Attack strategy

  14. Impact of JF Periodic Dropping Attack

  15. JF Delay Variance Attack • High delay will • cause TCP to send traffic in bursts due to “self-clocking,” leading to increased collisions and loss • cause mis-estimations of available bandwidth for delay-based congestion control protocols such as TCP Westwood and Vegas, • lead to an excessively high RTO value • Attack strategy • wait a random time before servicing each packet, maintaining FIFO order, but significantly increasing delay variance.

  16. Attack strategy

  17. Impact of JF Delay Variance Attack

  18. Black Hole Attacks (1) • Passive • Forwards routing packets • "Absorbs" all data packets • Hard to detect

  19. Black Hole Attacks (2)

  20. Misbehavior Diagnosis • Detection of MAC Layer Failure • Cross-layer design in DSR • Passive Acknowledgement (PACK) • Watchdog • Endpoint Detection • If severe loss detected • Can find the malicious guy?

  21. PACK • Energy Efficient Transmission: i cannot overhear j • Directional Antennas: j pretends to i to forward to k • Variable Power: j pretends to i to forward to k

  22. Victim Response • Establish an alternate path • Employ multipath routing • Establishment of backup routes

  23. Outline • Introduction and system model • DoS attacks • Analytical model • Evaluation • Related works • Conclusion

  24. Analytical Model • N nodes and pN nodes are JF or Black Holes • If the selected nodes represent a random sample of the N network nodes, then the path contains no attacking nodes with probability (1-p)h.

  25. Theoretical Results (1)

  26. Theoretical Results (2)

  27. Outline • Introduction and system model • DoS attacks • Analytical model • Evaluation • Related works • Conclusion

  28. Methodology • System fairness • Number of hops for received packets • Total system throughput • Probability of interception

  29. Baseline • 200 nodes move randomly in a 2000m×2000m topology • Maximum velocity of 10 m/s, pausing for 10 s on average. (Random Walk) • IEEE 802.11 MAC with a node receive range of 250 m. • 100 of these nodes communicate with each other to create 50 flows • UDP packets are transmitted at a constant rate of 800 bits/s, corresponding to one 500 byte packet every 5 s. • JF nodes are placed in grid

  30. JF Placement

  31. Distribution of the number of hops for received packets

  32. Fairness

  33. Average number of hops for received packets

  34. Extensive simulations • Offered Load and TCP • JellyFish Placement • Mobility • Node Density • System Size

  35. Related Work • Securing Routing Protocols • Usage of Multiple Routes • Securing Packet Forwarding

  36. Conclusion • TCP collapses with malicious • Dropping, reordering, jitter ... • More generally, all closed-loop mechanisms are vulnerable to malicious tampering • “Protocol-compliance” makes defense more problematic • First paper to quantify DoS effects on ad-hoc networks: • DoS increases capacity! BUT… • Network gets partitioned • Fairness decreases • System throughput, alone, is not enough to measure DoS impacts

More Related