Anomaly detection of communication link of mobile internet of things based on EM algorithm

Article type: Research Article

Authors: Li, Qian

Affiliations: Department of Electronics and Information Technology, Zhengde Polytechnic, Nanjing, Jiangsu 211106, China | E-mail: zdlq2021@163.com

Correspondence: [*] Corresponding author: Department of Electronics and Information Technology, Zhengde Polytechnic, Nanjing, Jiangsu 211106, China. E-mail: zdlq2021@163.com.

Abstract: The abnormality of communication link of mobile Internet of Things will threaten the security of communication of mobile Internet of Things, and the existing abnormality detection method is limited due to low accuracy, long time consumption and high energy consumption. To this end, the anomaly detection method of communication link of mobile Internet of Things based on EM algorithm is proposed in this study. Firstly, the anomaly range of the Internet of Things is located according to the communication node information of the data changes. Then the abnormal link of the target is judged and the anomaly feature of the communication link of the Internet of Things based on twin neural network is extracted. Finally, EM algorithm is improved with semi-supervised machine learning method to detect abnormal communication links of mobile Internet of Things. The experimental results show that the proposed method has the advantages of high precision, short time consumption and low energy consumption in the anomaly detection of communication links in the Internet of Things.

Keywords: EM algorithm, mobile internet of Things, communication link, anomaly feature extraction, anomaly detection

DOI: 10.3233/JCM-226416

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 1967-1979, 2022