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CCE Faculty Articles
An Adaptive Neural Swarm Approach for Intrusion Defense in Ad Hoc Networks
Document Type
Article
Publication Title
Proceedings of SPIE: Evolutionary and Bio-Inspired Computation: Theory and Applications V
ISSN
0277-786X
Publication Date
2011
Abstract
Wireless sensor networks (WSN) and mobile ad hoc networks (MANET) are being increasingly deployed in critical applications due to the flexibility and extensibility of the technology. While these networks possess numerous advantages over traditional wireless systems in dynamic environments they are still vulnerable to many of the same types of host-based and distributed attacks common to those systems. Unfortunately, the limited power and bandwidth available in WSNs and MANETs, combined with the dynamic connectivity that is a defining characteristic of the technology, makes it extremely difficult to utilize traditional intrusion detection techniques. This paper describes an approach to accurately and efficiently detect potentially damaging activity in WSNs and MANETs. It enables the network as a whole to recognize attacks, anomalies, and potential vulnerabilities in a distributive manner that reflects the autonomic processes of biological systems. Each component of the network recognizes activity in its local environment and then contributes to the overall situational awareness of the entire system. The approach utilizes agent-based swarm intelligence to adaptively identify potential data sources on each node and on adjacent nodes throughout the network. The swarm agents then self-organize into modular neural networks that utilize a reinforcement learning algorithm to identify relevant behavior patterns in the data without supervision. Once the modular neural networks have established interconnectivity both locally and with neighboring nodes the analysis of events within the network can be conducted collectively in real-time. The approach has been shown to be extremely effective in identifying distributed network attacks.
DOI
10.1117/12.883678
Volume
8059
NSUWorks Citation
Cannady, James D. Jr., "An Adaptive Neural Swarm Approach for Intrusion Defense in Ad Hoc Networks" (2011). CCE Faculty Articles. 447.
https://nsuworks.nova.edu/gscis_facarticles/447