基于特征节点分析的恶意节点检测算法研究

无线传感器网络(WSN)通常部署在复杂的环境中,攻击者很容易通过俘获节点注入虚假数据,造成严重后果。提出基于对事件源能量感知值相近的特征节点的恶意节点检测机制(DAFNA),首先对事件源的能量值进行估计,且在此过程中过滤保留良性特征节点;然后以特征节点为参照建立坐标系,通过分析待检测节点与事件源的距离计算值与距离感知值之间的差异,进行恶意节点的判断;最后通过仿真实验,对算法性能进行分析,并与Hur算法对比,得出DAFNA算法所需先验知识少,恶意节点容纳度更好。

Study on the malicious nodes detection algorithm based on feature nodes analysis

Wireless Sensor Network (WSN) is usually deployed in complex environment, and an attacker can easily inject false data by capturing nodes, thus causing serious consequences. A malicious nodes detection algorithm based on feature nodes analysis (DAFNA) is proposed. Firstly, the energy values of the event sources are estimated, and nodes healthy characteristics are maintained in this process. Secondly, we establish coordinates according to the feature nodes, conduct a variance analysis of the calculated and perceived distances between the nodes to be detected and the event source, thus the malicious nodes are identified. Simulation result verifies the effectiveness of the proposed algorithm, and compared with Hur algorithm it has a better accommodation of malicious nodes while requiring less prior knowledge.