A Danger Model Based Anomaly Detection Method for Wireless Sensor Networks

Wireless sensor network (WSN) is the hot research subject in the field of network technologies currently, and its security problem also attracts more attentions. Especially, intrusion detection in wireless sensor networks remains an open problem. In this paper, we study a novel danger model based anomaly detection algorithm for wireless sensor networks. The danger model is built on a sensitive tissue(ST). The sensitive tissue consists of a population of sensitive cells(SCs) that are abstracted characteristics from a node of wireless sensor networks which are sensitive to attacks. ST plays a role as an interface between problems and immune cells for danger recognition and estimation. The results of the application of this novel model to the detection of the syscalls data show that the model is valid.

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