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Surviving Attacks on Disruption-Tolerant Networks without Authentication

Surviving Attacks on Disruption-Tolerant Networks without Authentication. John Burgess , George Dean Bissias , Mark Corner, Brian Neil Levine. University of Massachusetts, Amherst. Goal. Understand DTN vulnerability Attack analysis Experimental evaluation. Disruption Tolerant Networks.

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Surviving Attacks on Disruption-Tolerant Networks without Authentication

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  1. Surviving Attacks on Disruption-Tolerant Networks without Authentication John Burgess,George Dean Bissias, Mark Corner, Brian Neil Levine University of Massachusetts, Amherst

  2. Goal • Understand DTN vulnerability • Attack analysis • Experimental evaluation

  3. Disruption Tolerant Networks • Networking for intermittently connected nodes • Rural Internet • Urban blind spots • Sparse sensor networks • Connectivity on a spectrum

  4. Unique Vulnerability • Measured by packet delivery rate • Nodes physically unsecured • Traditional defenses are inappropriate: • graph theoretical results are limited • identity management not always practical

  5. Weak Strong Attack strength Network impact Undisturbed Decimated Attack Universe • Weak attacks: • random node selection • easy to evaluate • Strong attacks: • optimal node selection • strong attack NP-hard to evaluate

  6. Outline • Attack Strategies • Data • Experimental Results • Conclusion

  7. Attacks: Weak • Nodes chosen at random • Attack defined by enumerating strategies • Remove Node • Drop all packets • Flood packets • Routing table falsification • ACK counterfeiting

  8. Attacks: Strong • Intractable to determine optimal attack set • Throughput is difficult metric to analyze • Even simple metrics lead to NP-hard problem • Instead, greedily remove vertices that most lower temporal connectivity

  9. Data: DieselNet • 40 buses • 802.11 protocol • 60 days of traces • Transmission events feed a simulator • Various routing protocols tested

  10. Data: Haggle • 41 devices in human mobility experiment • Bluetooth • 3 days of traces • Haggle connections more frequent than DieselNet • Haggle traces broken down to better match DieselNet

  11. Experiments: weak attack • Evaluated delivery rate via given routing protocol subject to given attack strategy • Used DieselNet data only Routing Protocols Attack Strategies • Remove node • Drop all • Flooding • Routing table Falsification • ACK counterfeiting

  12. Experiments: weak attack MaxProp • Minimum delivery rate above 20% • ACK counterfeiting is most effective attack

  13. Experiments: ACK Counterfeiting • Devise an ACK counterfeiting defense • ACKs should propagate after packets • Drop ACK if you haven’t seen packet yet • Defense improves minimum packet delivery rate • Drop All attack just as effective as ACK counterfeiting

  14. Experiments: strong attack • Seek to establish the validity of greedy attack • Find best k vertices in terms of temporal reachability via brute force evaluation for small k • Compare brute force results to greedy approach • Evaluate greedy attack for larger values of k • Evaluate both DieselNet and Haggle

  15. Experiments: strong attack Haggle: Brute vs. Greedy • For temporal reachability- best 5 nodes to remove almost always the same as 5 greedy choices • Results for DieselNet similar

  16. Experiments: strong attack Haggle: greedy attack • Displays roughly the same resilience to attack at DieselNet • Packet delivery rate degrades more slowly as more nodes are

  17. Conclusion • DTNs have unique susceptibility to attack • Susceptibility understood with attack analysis • Experiments on real traces show attack efficacy

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