A Study on Anomaly Data Traffic Detection Method for Wireless Sensor Networks

The massive growth of the Internet of Things applications recently has brought a lot of benefits to human society. Besides, the increase in the number of sensing devices in wireless sensor network infrastructure has created new challenges in ensuring wireless network security. Specifically, solutions to detect attacks from the edge of the network must be considered to reduce the pressure on the computing elements in core networks. Therefore, approximate approaches to low computational complexity in an Intrusion Detection System (IDS) need to be studied to favor limited-resource devices. In this paper, an intrusion detection model based on hedge algebra is proposed to detect anomaly sensory traffic. The numerical simulation results indicate that our proposed model achieves a higher rate of abnormal patterns than previous studies.