WSNs基于信誉机制的恶意节点识别模型

A reputation-based model for malicious node detection in WSNs

为了抵御无线传感器网络内部节点的拜占庭行为以及自私行为,针对现有恶意节点识别系统检测功能单一、不可抵御高信誉节点的恶意诽谤行为等问题.提出了一种无线传感器网络下的恶意节点识别模型,该模型采用Beta分布描述信誉分布,引入了第三方节点的间接可信度,并将多种攻击类型相对应的节点信任值进行整合.仿真实验表明,该模型能够更快更准确地识别出发起多种攻击的恶意节点,并在一定程度上抵御了高信誉节点的恶意诽谤行为.

To resist Byzantine behaviors and selfish behaviors of internal nodes, aimed at the problem that the existing malicious node detection systems can not resist the malicious deceit behaviors of high credit-grade nodes due to their single detection function, a reputation-based model for malicious node detection in WSNs is proposed. In this model, the beta distribution is used to describe the reputation distribution, the indirect reliability of the third-party nodes is introduced, and the trust values of nodes belonging to different types of attacks are integrated together. Simulation results show that the proposed model has better performance in terms of resisting the malicious deceit behaviors of high credit-grade nodes and identifying the malicious nodes which launch various types of attacks.