Detection of Distributed Attacks in Mobile Ad-Hoc Networks Using Self-Organizing Temporal Neural Networks
In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Artificial Intelligence
Mobile ad hoc networks continue to be a difficult environment for effective intrusion detection. In an effort to achieve reliable distributed attack detection in a resource-efficient manner a self-organizing neural network-based intrusion detection system was developed. The approach, Distributed Self-organizing Intrusion Response (DISIR), enables real-time detection in a decentralized manner that demonstrates a distributed analysis functionality which facilitates the detection of complex attacks against MANETs. The results of the evaluation of the approach and a discussion of additional areas of research is presented.
Cannady, James D. Jr., "Detection of Distributed Attacks in Mobile Ad-Hoc Networks Using Self-Organizing Temporal Neural Networks" (2010). CEC Faculty Articles. 448.