A Linear Systems Perspective on Intrusion Detection for Routing in Reconfigurable Wireless Networks

Abstract

Reconfigurable wireless networks, such as ad hoc or wireless sensor networks, do not rely on fixed infrastructure. Nodes must cooperate in the multi-hop routing process. This dynamic and open nature make reconfigurable networks vulnerable to routing attacks that could degrade significantly network performance. Intrusion detection systems consist of a set of techniques designed to identify hostile behavior. In this paper, there are several approaches for intrusion detection in reconfigurable network routing such as collaborative, statistical, or machine learning-based techniques. In this paper, we introduce a new approach to intrusion detection for reconfigurable network routing based on linear systems theory. Using this approach, we can discriminate routing attacks by considering the system's z-plane poles. The z-plane can be thought of as a two dimensional feature space that arises naturally. It is independent of the number of network attack detection metrics and does not require extra dimensionality reduction. Two different host-based intrusion detection techniques, inspired by this new linear systems perspective, are presented and analyzed through a case study. The case study considers the effects of attack severity and node mobility to the attack detection performance. High attack detection accuracy was obtained without increasing packet overhead for both techniques by analyzing locally available information.