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Artificial Intelligence
Data mining: practical machine learning tools and techniques with Java implementations
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Swarm intelligence: from natural to artificial systems
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The ant colony optimization meta-heuristic
New ideas in optimization
Ant algorithms for discrete optimization
Artificial Life
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MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
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Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing
Effective Intrusion Detection Using Multiple Sensors in Wireless Ad Hoc Networks
HICSS '03 Proceedings of the 36th Annual Hawaii International Conference on System Sciences (HICSS'03) - Track 2 - Volume 2
Implementation of an Intrusion Detection System Based on Mobile Agents
PDSE '00 Proceedings of the International Symposium on Software Engineering for Parallel and Distributed Systems
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WMCSA '99 Proceedings of the Second IEEE Workshop on Mobile Computer Systems and Applications
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SP '96 Proceedings of the 1996 IEEE Symposium on Security and Privacy
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WiSe '03 Proceedings of the 2nd ACM workshop on Wireless security
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Proceedings of the 1st ACM workshop on Security of ad hoc and sensor networks
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ICCNMC'05 Proceedings of the Third international conference on Networking and Mobile Computing
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IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Network: The Magazine of Global Internetworking
Reputation-based role assignment for role-based access control in wireless sensor networks
Computer Communications
Engineering Applications of Artificial Intelligence
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In this paper, we introduce FORK, a novel two-pronged strategy to an agent-based intrusion detection system for ad-hoc networks. We follow two different but complementary approaches for intrusion detection in our proposed scheme. We perform intrusion detection for power-aware ad-hoc networks. We introduce a novel power and reputation-based auctioning scheme for distributing agent-tasks in the network. Nodes compete for, and win auctions for performing the tasks based on a competitive power-efficient mechanism that permits collaboration between nodes. The chosen nodes perform the intrusion detection using our proposed anomaly detection algorithm that is modeled on popular evolutionary algorithms techniques. We evaluate our system both in terms of the task allocation algorithm as well as results of actual intrusion detection performed in some session log files. The outcome is promising and offers scope for some interesting additional research.