摘要
针对无线传感器网络中恶意节点的检测识别问题,提出一种似然多元分类的无线传感器网络动态恶意节点检测算法。分析恶意节点的异常状态信息,提取恶意节点的特征属性;对恶意节点的攻击模式进行建模,结合似然多元分类算法和贝叶斯规则求出节点类型划分的最终判别函数。实验结果表明,相比移动恶意攻击节点分布式检测方案和基于重复博弈的恶意节点检测算法,该算法在检测和识别恶意节点上具有更高的准确度和更低的平均检测错误率。
To solve the problems of detection and identification of malicious nodes in wireless sensor networks,a dynamic malicious node detection algorithm based on likelihood multivariate classification in wireless sensor network was proposed.The abnormal state information of malicious nodes was analyzed to extract feature attributes of malicious nodes.Attack modeling of malicious nodes was modeled,and the likelihood multivariate classification algorithms and Bayes' rule were combined to find final discriminant function of node classification.Simulation results show that compared with mobile malicious attacks nodes distributed detection scheme and malicious node detection algorithm based on repeated games,the proposed method has higher accuracy and lower average detection error rate in detection and identification of malicious nodes.
引文
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