Misbehaviour Detection in Cognitive and Cooperative Networks

This paper presents an approach to detect misbehaving nodes in cognitive and cooperative networks. In particular, we propose a cooperative scheme, where cognitive radios are granted access in licensed bands, as long as they compensate primary (licensed) users for the additional interference generated in their bands through cooperation. However, this cooperative transmission can be vulnerable to malicious attacks, which are not easy to detect, since they may affect the error probability experienced by the primary users, but not their signal to noise and interference ratio. We propose a misbehavior detection approach based on measuring and comparing the entropy of data derived by anomalous and normal behaviors. Simulation results show that the probability of detection strongly depends on the transmission power and spectrum handoff rate of the outliers.