Mitigating routing misbehavior in mobile ad hoc networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
PGP: Pretty Good Privacy
A logic for uncertain probabilities
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Securing ad hoc routing protocols
WiSE '02 Proceedings of the 1st ACM workshop on Wireless security
The Resurrecting Duckling: Security Issues for Ad-hoc Wireless Networks
Proceedings of the 7th International Workshop on Security Protocols
Security-Aware Ad hoc Routing for Wireless Networks
Security-Aware Ad hoc Routing for Wireless Networks
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ACSC '04 Proceedings of the 27th Australasian conference on Computer science - Volume 26
Trust based adaptive on demand ad hoc routing protocol
ACM-SE 42 Proceedings of the 42nd annual Southeast regional conference
Black hole attack in mobile Ad Hoc networks
ACM-SE 42 Proceedings of the 42nd annual Southeast regional conference
LCN '04 Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks
Routing security in wireless ad hoc networks
IEEE Communications Magazine
IEEE Transactions on Neural Networks
Analytical models for trust based routing protocols in wireless ad hoc networks
ACM SIGSOFT Software Engineering Notes
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International Journal of Wireless and Mobile Computing
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This paper presents a guard node based scheme to identify malicious nodes in Ad hoc On-Demand Distance Vector (AODV) protocol. In this scheme each node calculates trust level of its neighboring nodes for route selection. Trust calculation process involves opinions of other nodes about the node whose trust level is to be determined. If a neighboring node has a trust level lower than a predefined threshold value, it is identified as malicious and it is not considered for route selection. The proposed model does not use any key distribution process and no changes are made in control packets of AODV. Simulation results show that the proposed scheme improves performance of AODV by identifying and removing malicious nodes. Performance of the scheme has been evaluated for three different types of malicious attacks (impersonation attack, colluding nodes attack and black hole attack).