Indirect Reciprocity Security Game for Large-Scale Wireless Networks

Abstract

Radio nodes can obtain illegal security gains by performing attacks, and they are motivated to do so if the illegal gains are larger than the resulting costs. Most existing direct reciprocity-based works assume constant interaction among players, which does not always hold in large-scale networks. In this paper, we propose a security system that applies the indirect reciprocity principle to combat attacks in wireless networks. Because network access is highly desirable for most nodes, including potential attackers, our system punishes attackers by stopping their network services. With a properly designed social norm and reputation updating process, the aim is to incur a cost due to the loss of network access to exceed the illegal security gain. Thus rational nodes are motivated to abandon adversary behavior for their own interests. We derive the optimal strategy and the corresponding stationary reputation distribution, and evaluate the stability condition of the optimal strategy using the evolutionarily stable strategy concept. This security system is robust against collusion attacks and can significantly reduce the attacker population for a wide range of attacks when the stability condition is satisfied. Simulation results show that the proposed system significantly outperforms the existing direct reciprocity-based systems, especially in the large-scale networks with terminal mobility. This technique can be extended to many wireless networks, including cognitive radio networks, to improve their security performance.