Anomaly Detection of IoT Communication Equipment Based on Entropy Ideal Point Method: from the Perspective of Quantum Communication

Abstract

In this paper, the entropy weight method is used to calculate the weight of each evaluation index, and a soft foundation treatment plan decision model based on the ideal point method based on the entropy weight is established. An anomaly data detection method based on the ideal point method based on entropy weight is proposed. In the process of classifying massive anomalous data, multiple constraints that can constrain the abnormal characteristics of tags are introduced, and the dimensionality reduction and restriction processing of IoT communication data is performed to avoid expansion. The search process is optimized, and the support vector machine is used to complete the detection and classification in the restricted area. Experimental results show that using this algorithm can search for massive amounts of IoT communication anomaly data in an automatic learning process, and improve the accuracy of anomaly data detection.