Fuzzy-based Energy Efficient Method for Multiple Attacks in Sensor Networks: against False Vote and Report Injection Attacks

An adversary can easily compromise sensor nodes in wireless sensor networks, and generate multiple attacks through compromised nodes, such as false vote injection attacks and false report injection attacks. The false vote injection attack tries to drop legitimate reports in an intermediate node, and the false report injection attack tries to drain the energy consumption of each node. To prevent these attacks, a probabilistic voting-based filtering scheme (PVFS) has been proposed to select verification nodes, and to detect fabricated votes in the reports as they occur simultaneously. In this paper, we propose a method that improves the energy efficiency of each node and the security level of the false report injection attack, while maintaining the detection power of the false vote injection attack. Our proposed method effectively selects verification node with considering the conditions of each node, based on a fuzzy rule-based system. The verification node is decided through the energy remaining level, distance level, and number of detected false votes in the fuzzy system. We evaluated the effectiveness of the proposed method, as compared to PVFS, when two attacks occur simultaneously in the sensor network. The experimental results show that our method saves energy by up to 8%, by improving and maintaining the defence against these multiple attacks.