Game-Theoretic Security Analysis in Heterogeneous IoT Networks: A Competition Perspective
Yuyao Zhu, Huici Wu, Xiaofeng Tao, Shen Wang · IEEE Internet of Things Journal · 2024
Many interconnected terminals in the Internet of Things (IoT) networks raise significant security risks. From a competitive perspective, the many heterogeneous nodes, including various wireless terminals, access points, and base stations are the competing targets between the defenders and potential attackers. This article proposes a security competition model based on the game theory to address the security competition problem. The model has two players, a defender and an attacker, who allocate resources to each IoT node according to their strategies. A novel metric, security entropy, derived from the security probability, quantifies each node’s security status. Based on the node heterogeneity, the overall security performance of the considered IoT network is evaluated with a topology-determined weighted security entropy. The defender and the attacker, respectively, aim to decrease and increase the weighted security entropy while balancing the cost, which constitutes their utility functions. The existence of the unique Nash equilibrium is proved. A best response selection algorithm for the optimal solutions is designed. The experimental results demonstrate that the proposed model effectively represents the goal orientation and interaction between the attackers and defenders in various scenarios. Additionally, increasing the cost for the attackers significantly reduces their resource allocation, especially to the attackers leading to a decrease in the system’s security entropy.