基于特征节点分析的恶意节点检测算法研究  

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

作　　者：谢晋阳[1] 李平[1] 谢桂芳[2] 

机构地区：[1]长沙理工大学计算机与通信工程学院,湖南长沙410004 [2]湘南学院计算机系,湖南郴州423000

出　　处：《计算机工程与科学》2015年第1期78-83,共6页Computer Engineering & Science

基　　金：国家973计划资助项目(2011CB302902);国家自然科学基金资助项目(61073180)

摘　　要：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。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.

关 键 词：无线传感器网络 能量感知 虚假数据 特征节点 恶意节点 

分 类 号：TP212.9[自动化与计算机技术—检测技术与自动化装置]