A routing game in Cognitive Radio Networks against Routing-toward-Primary-User Attacks

This paper proposes a robust, spectrum-aware routing mechanism for the multi-hop, multi-channel Cognitive Radio Networks (CRNs) that are exposed to the Routing-toward-Primary-User Attack (RPUA). With RPUA, malicious Secondary Users (SUs) attempt to block the data transmission of the normal SUs by routing packets towards the SUs around the Primary Users (PUs). The proposed routing mechanism models the interaction between the non-malicious SUs and their one-hop neighbors as a stochastic game. With routing information back-propagation from the next-hop SUs, the local relay-channel-selection games along the routing path form a global, layered Markov Decision Process (MDP). To address the problem of the mixed attack with both RPUA and Sink-Hole-Attack (SHA), the trustworthiness of the neighbor nodes is evaluated as a single-buyer-multiple-seller price competition. For each SU, the best policy of relay-channel selection is learned in a reinforcement learning framework with fictitious play. Simulation results show that the proposed routing algorithm can avoid malicious relays and minimize the routing delay in the CRN under attacks.