无线传感器网络中基于安全数据融合的恶意节点检测

无线传感器网络的一些固有特点,如节点能量、存储空间和计算处理能力均有限,网络节点布署在野外而无人值守,节点易被敌方捕获,因而网络内部易存在恶意节点。本文在分析Atakli等人提出的WTE方案基础上,提出了一种新的基于安全数据融合的恶意节点检测算法(MNDSDF)。针对节点数目较多层次型的无线传感器网络,MNDSDF算法首先在WTE权值融合的思想上添加了高信誉值过滤机制,来检测恶意采集节点;其次针对WTE和WCF只允许簇内单跳和融合结果受恶意节点影响较大等不足,提出了数据包计数的策略,来检测恶意转发节点。与WTE相比,MNDSDF算法能抵制更多种攻击行为,适应更宽泛的路由协议。通过仿真实验,MNDSDF算法可以有效检测出部分恶意行为,并经过与WTE和WCF比较,具有更高检测率和更低误检率。

Malicious Nodes Detection Algorithm based on Secure Data Fusion in Wireless Sensor Networks

Having the inherent characteristics of wireless sensor networks, such as limitation of node energy, storage space and computing capacity and unattended in the open air, network nodes are easily captured by the enemy, malicious nodes exist within the network easily. Based on the analysis of the WTE algorithm proposed by Idris, this paper proposes a Malicious Nodes Detection algorithm based on Secure Data Fusion (MNDSDF). Compared with the WTE, MNDSDF algorithm can resist various attacks, and be adapt to more routing protocols. Simulation experiment shows that MNDSDF can effectively detect the malicious behavior, and it has a higher detection rate and lower false detection rate compared with WTE and WCF.