Abstract
We present a study of using game theory for protecting wireless sensor networks (WSNs) from selfish behavior or malicious nodes. Due to scalability, low complexity and disseminated nature of WSNs, malicious attacks can be modeled effectively using game theory. In this study, we survey the different game-theoretic defense strategies for WSNs. We present a taxonomy of the game theory approaches based on the nature of the attack, whether it is caused by an external attacker or it is the result of an internal node acting selfishly or maliciously. We also present a general trust model using game theory for decision making. We, finally, identify the significant role of evolutionary games for WSNs security against intelligent attacks; then, we list several prospect applications of game theory to enhance the data trustworthiness and node cooperation in different WSNs.
Highlights
Security and authentication in Wireless Sensor Networks (WSNs) face a more challenging environment compared to traditional networks
We have addressed the important and challenging problem of assuring trustworthiness of sensor data in the presence of both selfish behavior and malicious adversaries in wireless sensor networks (WSNs)
We have carried out an extensive overview of the state-of-the-art of many game theoretic approaches that are utilized to design defense strategies to protect sensor nodes from attacks and to guarantee a high level of trustworthiness for sensed data
Summary
Security and authentication in Wireless Sensor Networks (WSNs) face a more challenging environment compared to traditional networks. We study the game theory based approaches for mitigating different WSN security threats from the state-of-the-art literature on the topic. We classify those approaches into two main categories, namely, cooperative games and non-cooperative games, and each summarizes the involved defense strategies based on game theory. A general trust model based on the discussed game theory approaches and scenarios is introduced to take into account the variability and features of the attack types.
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