Multivariate Classification-Based Malicious Node Detection for Wireless Sensor Network
Hongjun Dai · Chuangan jishu xuebao · 2011
Wireless Sensor Network(WSN)is a distributed network exposed to an open environment.In a WSN,there are few central nodes or monitoring nodes and each node is independent.So WSNs are vulnerable to malicious nodes.In order to find out malicious nodes among a wireless sensor network with mass sensor nodes,this paper presents a malicious detection method based on multivariate classification.Given the types of a few sensor nodes,it extracts sensor nodes' preferences related with the known types of malicious node,establishes the sample space of all sensor nodes that participate in network activities.Then,according to the study on the type-known sensor nodes' samples based on the multivariate classification algorithm,a classifier is generated,and all the unknown-type sensor nodes are classified.The experiment results show that as long as the value of sensor nodes preferences and the number of active sensor nodes is stable,the false detection rate is stabilized under 0.5%.