1 / 25

Cooperative and Reliable Packet-Forwarding on Top of AODV

Cooperative and Reliable Packet-Forwarding on Top of AODV. Bracha Hod March 2006. Outline. Background Mobile ad hoc network Ad-hoc On Demand Distance Vector Trust and reputation Problem statement Solution Misbehaving detection Reputation system Misbehavior reaction

Télécharger la présentation

Cooperative and Reliable Packet-Forwarding on Top of AODV

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.


Presentation Transcript

  1. Cooperative and Reliable Packet-Forwarding on Top of AODV Bracha Hod March 2006

  2. Outline • Background • Mobile ad hoc network • Ad-hoc On Demand Distance Vector • Trust and reputation • Problem statement • Solution • Misbehaving detection • Reputation system • Misbehavior reaction • Simulation results • Conclusions

  3. Mobile Ad hoc Network • An autonomous, self-configuring system of mobile devices (laptops, smart phones, sensors, etc.) connected by wireless links • Each node operates as both an end-system and a router • MANET characteristics: • Mobility and dynamic topology • Bandwidth-constrained • Energy-constrained • Prone to security threats

  4. Mobile Ad hoc Network

  5. MANET Routing Protocols • Proactive/Table-driven • Periodically broadcast information across the network in a controlled flood • Waste bandwidth and power consumption • Reactive/On-demand • Initiate a route only when it is required • Delay when building new routes

  6. Ad-hoc On-demand Distance Vector • RFC 3561 (2003) • One of the leading protocols for MANET • Uses sequence numbers to avoid loops • Quick adaptation to dynamic networks • Low processing and memory overhead • Scalable

  7. AODV Route Discovery Route Request Reverse Route Route Reply A B C D G E F

  8. AODV Route Maintenance Hello Message Route Error A B C D G E F

  9. Trust and Reputation • Trust • A subjective expectation a node has about another node’s future behavior, based on the history of their encounters • Reputation • A perception that a node creates through past actions about its intentions and norms • Reputation System • A system in which the nodes who participate in it compute rating values and then advertise these values among the other nodes

  10. Problem Statement • MANET is vulnerable to many attacks • Packet dropping is the most common attack • Motivation to misbehave • Selfish nodes are interested in saving their battery life • Malicious nodes aim to damage other nodes • Misbehavior patterns we handle • Black hole node advertises itself as part of a path and then drop the packets • Gray hole node adversary selectively drops some packets but not other

  11. Solution • Misbehavior Detection • Watch the neighbors and record their behavior • Reputation System • Maintain direct rating according to the observations • Exchange rating among nodes • Incorporate direct and indirect rating • Use trust information • Misbehavior Reaction • Classify nodes • Select reliable paths • Punish misbehaving nodes

  12. First-Hand Observations • Overhear neighbors • Direct mode – getting packets explicitly • Promiscuous mode • Examine the overheard packets • Update the positive and negative actions i k j h

  13. Direct Rating • Calculation and management of the rating using the Beta distribution function • Direct rating of a node j by its neighbor i

  14. Rating Exchange • Local model as a result of MANET constrains • Reputation distribution is performed continuously • Neighbors’ direct rating and a black list of misbehaving nodes are exchanged among 1-hop neighbors • Limited detection and punishment in large and mobile networks

  15. Trust • Misbehaving nodes might spread false rating information • The trust estimates the reliability of the reports

  16. Second-Hand Observations • Accept indirect rating DRk,j if the node is trusted or if it passes the deviation test • Estimate of the indirect positive and negative actions based on the indirect rating • Combine the direct and indirect rating to a total rating

  17. Misbehavior Reaction • Nodes’ classification • Total rating value with total positive and negative actions • Two nodes with the same total rating, but with different history are classified differently • Path selection • Greedy selection of the next hop • Path maintenance for partial dropping • Punishment of misbehaving nodes • Second chance when the rating is faded

  18. Simulation Model • Simulation in GloMoSim • Standard parameters of the channel and radio model • IEEE 802.11 as the medium access protocol • Nodes are places randomly in the area • Movement by random waypoint model • Speed range of 5-20 m/s • Pause time range of 0-500s • Data packets transmission at constant bit rate (CBR) on routes above 1-hop length

  19. Throughput of Well-behaving Nodes 50 Nodes 100 Nodes 15 Sources, 15 Black-holes 20 Sources, 30 Black-holes

  20. Punishment of Misbehaving Nodes Data Packets Transmitted Data Packets for by Misbehaving Nodes Misbehaving Nodes That were not Transmitted 50 Nodes, 15 Sources, 15 Black-holes

  21. Partial Dropping (Gray holes) Data Packets Dropped Dropping percentage of 50% Different Dropping (32% of the total rating) Percentages 50 Nodes, 15 Sources, 15 Gray-holes

  22. Robustness against Advanced Liars Data Packets Received False Positives 50 Nodes, 15 Sources, 10 Black-holes

  23. Scalability over AODV Throughput Data Packets Dropped 500 Nodes, 250 static and the remainder walk on speed of 5-10 m/s. 30 Sources, 50 black holes

  24. Conclusions • A reputation system on top of AODV is effective for both partial and complete dropping • The reputation system remained robust against advanced liars, when a majority of the nodes are trustworthy • In large and unstable networks, it is better to rely on self-observations because the network conditions have greater effect than the reputation system benefits

  25. Thank you!

More Related