Malicious node detection in wireless sensor networks using time series analysis on node reputation

نویسندگان

  • Li Dan
  • Xin Yang
چکیده

Because of wireless sensor networks are usually deployed in hostile environment without continuous supervision, node compromise is the most critical threats of security issues of wireless sensor networks. In this paper, we proposed a method to identify malicious nodes in wireless sensor networks which have deployed with a reputation system through using time series analysis on node reputation. We focus a tricky type of attack nodes in reputation sensor network. These nodes can launch attacks or abnormal behaviors abstemious to against the detection of reputation system. We give a detail of definition of these nodes in the paper and call them sub-aggressiveness malicious nodes. Our scheme to identify these nodes combined time series analysis with k-means clustering. With a series simulation, the results reveal that the proposed scheme has good performance and effectiveness to identify sub-aggressiveness malicious nodes which are hardly to be detected by reputation threshold mechanism of reputation network.

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تاریخ انتشار 2012