A biologically-inspired type-2 fuzzy set based algorithm for detecting misbehaving nodes in ad-hoc wireless networks

Implementation of routing protocols in mobile adhoc networks relies on efficient node cooperation. However, node misbehavior is a common phenomenon, thus, ad-hoc networks are subject to packet dropping, packet modification, packet misrouting, selfish node behavior, and so on. In this paper, a biologically-inspired type-2 fuzzy set recognition algorithm for detecting misbehaving nodes in an ad-hoc wireless network is presented. Such algorithm, inspired by danger theory and antigen presenting cells, would be implemented in an Artificial Immune System (AIS) for detecting misbehaving nodes without human intervention.

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