Benefit from the rapidly developing in hardware manufacturing technology and efficient software algorithms, wireless sensor networks have been widely used in many fields. Secure routing protocol in wireless sensor network has been an essential issue to consideration when security requirements are rising in deployments of sensor networks. But, in the early period, security aspects in routing protocol have not been given enough attention. So, many routing protocols of WSNs since design stage have not taken secure requirements in mind. In this paper, we proposed a secure routing protocol based on node reputation of wireless sensor network, and enlightened by the idea of ant colony optimization, the routing protocol named Reputation-based Ant secure routing protocol (RBASR). This routing protocol simulates an ant system to find the optimum route path of wireless sensor network. Distinguish from a real ant colony, RBASR use reputations of nodes as a special pheromone to evaluate rating of a path. Consider with other flexible requirements, protocol setup the optimum routing path of data transferring between the sources to the destination.

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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