A Malicious Node Detection Algorithm Based on Principle of Maximum Entropy in WSNs

WSN is a distributed network exposed to an open environment, which is vulnerable to malicious nodes. To find out malicious nodes among a WSN with mass sensor nodes, this paper presents a malicious detection method based on maximum entropy model. Given the types of a few sensor nodes, it extracts sensor nodes’ preferences related with the known types of malicious node, establishes the maximum entropy model of all sensor nodes that participate in network activities. Then, according to the study on the type-known sensor nodes’ samples based on principle of maximum entropy, all of the unknown-type sensor nodes are classified, with probabilities of different types. The experiment results show that as long as the preferences of sensor nodes are precise and the number of active sensor nodes is stable, the detection rate of malicious nodes is stabilized over 90%.