Signaling game based strategy of intrusion detection in wireless sensor networks

As Wireless Sensor Networks (WSNs) become increasingly popular, it is necessary to require Intrusion Detection System (IDS) available to detect internal malicious sensor nodes. Because sensor nodes have limited capabilities in terms of their computation, communication, and energy, selecting the profitable detection strategy for lowering resources consumption determines whether the IDS can be used practically. In this paper, we adopt the distributed-centralized network in which each sensor node has equipped an IDS agent, but only the IDS agent resided in the Cluster Head (CH) with sufficient energy will launch. Then, we apply the signaling game to construct an Intrusion Detection Game modeling the interactions between a malicious sensor node and a CH-IDS agent, and seek its equilibriums for the optimal detection strategy. We illustrate the stage Intrusion Detection Game at an individual time slot in aspects of its player’s utilities, pure-strategy Bayesian–Nash equilibrium (BNE) and mixed-strategy BNE. Under these BNEs the CH-IDS agent is not always on the Defend strategy, as a result, the power of CH can be saved. As the game evolves, we develop the stage Intrusion Detection Game into a multi-stage dynamic Intrusion Detection Game in which, based on Bayesian rules, the beliefs on the malicious sensor node can be updated. Upon the current belief and the Perfect Bayesian equilibrium (PBE), the best response strategy for the CH-IDS agent can be gained. Afterward, we propose an intrusion detection mechanism and corresponding algorithm. We also study the properties of the multi-stage dynamic Intrusion Detection Game by simulations. The simulation results have shown the effectiveness of the proposed game, thus, the CH-IDS agents are able to select their optimal strategies to defend the malicious sensor nodes’ Attack action.