关键词: 无线传感器网络, 极限学习机, 混合, 入侵检测, 信任管理, 分簇

Abstract: Based on the study of machine learning algorithm,this paper proposes a hybrid intrusion detection scheme using the Extreme Learning Machine(ELM)for Wireless Sensor Network(WSN). It divides the WSN into the perception layer,data aggregation layer and the core control layer,corresponding intrusion detection scheme is presented at each layer.Especially,in the core control layer,it sets trust management modules and ELM modules. Using a trust module can timely sieve to abnormal nodes. The ELM is faster than the SVM algorithm,and the efficiency of intrusion detection can be further improved when using ELM. Experimental results show that the scheme that combines the ELM with traditional intrusion detection technology balances the advantages and disadvantages,reduces the energy consumption and prolongs the network uptime,on the basis of guaranteeing a higher detection rate. So it is more suitable for WSN which is resource-constrained.

Key words: Wireless Sensor Network(WSN), Extreme Learning Machine(ELM), hybrid, intrusion detection, trust management, clustering