Prethodno priopćenje

https://doi.org/10.17559/TV-20230228000387

Anomaly Detection in Wireless Sensor Networks Based on Improved GM Model

Hongzhang Han ; School of Computer Engineering, Jiangsu University of Technology, Changzhou 213001, China
Zhengjun Jing ; School of Computer Engineering, Jiangsu University of Technology, Changzhou 213001, China

Sažetak

Aiming at the problems of poor detection effect, high rate of missed detection and high rate of false detection in traditional methods, an anomaly detection method for wireless sensor networks based on improved GM model is proposed. The multilateral measurement method is used to locate the nodes in the wireless sensor network, and the state tracking of the running track of the located nodes is carried out. According to the tracking results, the self similarity between nodes is measured by Hurst index. Based on the measurement results, the improved GM model is used to predict the abnormal nodes. The abnormal values of the wireless sensor network are calculated by the distance between adjacent points, and the state of the current node is judged, this completes the anomaly detection of wireless sensor networks. The experimental results show that the proposed method is effective in anomaly detection of wireless sensor networks, and the rate of missed detection and false detection is low.

Ključne riječi

hurst index; network anomaly; node positioning; self similarity; wireless sensor

Hrčak ID:

305492

URI

https://hrcak.srce.hr/305492

Datum izdavanja:

28.6.2023.

Posjeta: 286 *