Vulnerability analysis and security framework (BeeSec) for nature inspired MANET routing protocols
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Identification of malicious nodes in an AODV pure ad hoc network through guard nodes
Computer Communications
A sense of danger: dendritic cells inspired artificial immune system for manet security
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Monitoring assisted robust routing in wireless mesh networks
Mobile Networks and Applications
Agent-based modeling of host-pathogen systems: The successes and challenges
Information Sciences: an International Journal
Anti-virus security and robustness of heterogeneous immune static network
Proceedings of the 5th International ICST Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness
Danger theory based SYN flood attack detection in autonomic network
Proceedings of the 2nd international conference on Security of information and networks
A novel immune inspired approach to fault detection
ICARIS'07 Proceedings of the 6th international conference on Artificial immune systems
BeeAIS: artificial immune system security for nature inspired, MANET routing protocol, BeeADHoc
ICARIS'07 Proceedings of the 6th international conference on Artificial immune systems
Agent-based artificial immune system approach for adaptive damage detection in monitoring networks
Journal of Network and Computer Applications
Real-time detection of traffic anomalies in wireless mesh networks
Wireless Networks
Eliminating misbehaving nodes by opinion based trust evaluation model in MANETs
Proceedings of the 2011 International Conference on Communication, Computing & Security
Misbehaving nodes detection through opinion based trust evaluation model in MANETs
Proceedings of the International Conference & Workshop on Emerging Trends in Technology
Immunizing mobile ad hoc networks against collaborative attacks using cooperative immune model
Security and Communication Networks
Artificial immune system based mobile agent platform protection
Computer Standards & Interfaces
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In mobile ad hoc networks, nodes act both as terminals and information relays, and they participate in a common routing protocol, such as dynamic source routing (DSR). The network is vulnerable to routing misbehavior, due to faulty or malicious nodes. Misbehavior detection systems aim at removing this vulnerability. In this paper, we investigate the use of an artificial immune system (AIS) to detect node misbehavior in a mobile ad hoc network using DSR. The system is inspired by the natural immune system (IS) of vertebrates. Our goal is to build a system that, like its natural counterpart, automatically learns, and detects new misbehavior. We describe our solution for the classification task of the AIS; it employs negative selection and clonal selection, the algorithms for learning and adaptation used by the natural IS. We define how we map the natural IS concepts such as self, antigen, and antibody to a mobile ad hoc network and give the resulting algorithm for classifying nodes as misbehaving. We implemented the system in the network simulator Glomosim; we present detection results and discuss how the system parameters affect the performance of primary and secondary response. Further steps will extend the design by using an analogy to the innate system, danger signal, and memory cells.