Detection of Wormhole Attacks in Wireless Sensor Networks Based on Anomaly Detection Algorithms

Abstract

Wireless sensor networks(WSN) are facing potential threats of various attacks, among which wormhole attack is one of the most harmful attacks. Wormhole attack is hard to detect, and once they occur, a series of other attacks will be carried out to discard, steal, and tamper with messages on the network. Due to the limited resources and computing power of WSN nodes, it has higher requirements for defense algorithms. However, existing solutions either require additional hardware, or require higher communication overhead, or perform badly in the wormholes with short hops. This paper proposes an anomaly detection algorithm based on mean-shift and median absolute deviation(MSAMAD), which detects wormhole attacks by detecting the abnormal number of forwarding and the abnormal single-hop time between nodes. MSAMAD does not require special hardware and strict time synchronization, and the communication overhead is small. The simulation results show that this method has a high detection rate, especially in short-range wormhole attacks more than other methods.