Advanced Path Selection Method for Detection of False Reports in Statistical Filtering Based WSNs

Abstract

Sensor nodes communicate with each other via wireless channels, which are not particularly secure. Accordingly, sensor nodes are vulnerable to physical attacks, potentially compromising the node’s keys. An adversary can capture deployed nodes and inject the false reports using captured nodes. False reports attacks can lead not only false alarms, but also the depletion of energy resource of nodes. Yet et al. proposed statistical en-route filtering scheme to filter out such false report in en-route process. Several research efforts to improve the detection power of SEF have been made. Sun et al. proposed a path selection method (PSM) for improving the detection power of SEF using a control message contained the key information of visited nodes. However, the key information does not be updated or reset in the flooding process. Consequently, nodes which are located far from the sink cannot evaluate accurate quality of the incoming path and choose the secure paths. In this paper, we proposed an advanced path selection method for improving the detection power of PSM using two partition arrays and information of downstream nodes of forwarding node. By using this information, each node evaluates and chooses the most secure paths. To show the effectiveness, we have compared the proposed method with the two existing methods, SEF and PSM, in terms of filtering ratio of false reports and energy consumption for detection by providing simulation results.