Honeypot-based defense strategy in IoT networks using Signaling game
Haoyuan Liu, Hao Wu · 2024
In the context of the flourishing Internet of Things (IoT) technology, the extensive deployment of IoT devices, along-side their limited defense capabilities, renders them vulnerable targets for malicious hacker attacks. In order to deal with some powerful hackers, honeypot technology is often applied in IoT security defense. However, since running and maintaining honeypot technology will bring some overhead, finding a secure and efficient strategy to apply it has been a major challenge. In this paper, we model the interaction between an attacker and a defender as a signaling game, aiming to examine how the network defender selects the optimal defense strategy when faced with resource constraints. We develop a Dynamic Defense Strategy algorithm tailored to the capabilities of diverse attackers drawing on perfect Bayesian Nash equilibrium. Extensive simulation experiments demonstrate that our proposed dynamic strategy, based on the signaling game model, outperforms the traditional random or maximum defense strategy in terms of both defense effectiveness and cost.