Chung Il Sun

A secure path determination method for statistical en-route filtering based wireless sensor network

Wireless sensor networks usually operate in open and unattended environments without infrastructure; hence, they are vulnerable to physical attacks. In false report injection attacks, adversaries inject false reports into networks by using compromised nodes in these networks. Such attacks cause not only false alarms, but they also shorten the networks life. The statistical en-route filtering scheme aims to detect and drop false reports en route. In the routing process, each forwarding node performs a role that verifies event reports utilizing its own keys and drops false reports. Therefore, path selection to transmit event reports can be an important element for guaranteeing network security. In this paper, we propose a secure path determination method for statistical en-route filtering based wireless sensor networks. According to the proposed method, the base station floods route messages that contain information of a forwarding path. According to the result of evaluation functions based on obtained information, each node chooses a path with consideration to security and energy efficiency. The effectiveness of the proposed method against false injection attacks is shown via simulation results.

Advanced path selection method for detection of false reports in statistical filtering based WSNs

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 nodes 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 etal. 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 etal. 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.