Evolutionary Game-Based Secrecy Rate Adaptation in Wireless Sensor Networks

Guanxiong Jiang, Shigen Shen, Keli Hu, Longjun Huang, Hongjie Li and Risheng Han

International Journal of Distributed Sensor Networks, 2015, vol. 11, issue 3, 975454

Abstract: Physical layer security, whose aim is to maximize the secrecy rate of a source while keeping eavesdroppers ignorant of data transmitted, is extremely suitable for Wireless Sensor Networks (WSNs). We therefore, by developing the classical wire-tap channel, construct an approach to compute the secrecy rate between a sensor node and its responsible cluster head in the clustered WSNs. A noncooperative secrecy rate game towards WSNs is formulated to solve contradictions between maximizing the secrecy rate of a sensor node and minimizing power consumed for data transmission. Using evolutionary game theory, we set up a selection dynamics upon which a power level can be adaptively selected by a sensor node. Thus, the objective of secrecy rate adaptation for maximizing the fitness of member sensor nodes is achieved. We also prove the game is stable; that is, there exist evolutionarily stable strategies (ESSs) that explain which strategies will be selected by a sensor node in the end. Moreover, a corresponding algorithm of secrecy rate adaptation is given. Numerical experiments show our proposed approach can adaptively adjust the secrecy rate of a sensor node, which provides a novel way to guarantee the confidentiality of WSNs.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:11:y:2015:i:3:p:975454

DOI: 10.1155/2015/975454

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