A Wormhole Attacks Detection Using a QTS Algorithm with MA in WSN

Abstract

Wireless sensor networks (WSN) can be widely used in many areas, such as environment monitoring, weather forecasting, traffic control, etc. The wormhole attack problem is an important issue in WSN since it causes many problems, such as routing error, a reduction in sensor lifetime and broken network topology. Several wormhole detection approaches have been proposed, but most of them need special hardware devices and consume a lot of system resources. This paper proposes a novel and efficient method to detect the wormhole attack without hardware equipment or requiring much information about WSN. The proposed method uses a moving average (MA) indicator, which has been commonly used in financial fields, to apply to neighbors of sensor nodes, it becomes a dynamic detection indicator of the number of neighbor nodes. Because the combinations are too numerous to arrange, we utilize a Quantum-inspired Tabu Search (QTS) algorithm. This algorithm is efficient and effective in finding the ideal combination of detection indicators to detect wormhole attacks in different scenarios. The simulation result shows our method is intuitive and efficiently detects wormhole.