Detection for Nodes Intrusion of Compressed Transmission Data Based on Fuzzy Analytic Hierarchy Process

In order to overcome the problems of low clustering accuracy, low detection efficiency and low detection accuracy in the traditional intrusion detection method for compressed transmission data nodes. This paper proposes an intrusion detection method based on fuzzy analytic hierarchy process. Based on the first-order RF energy consumption model, this method calculates the optimal number of cluster heads, and combines GWO algorithm and FCM algorithm to divide the network into clusters to achieve the clustering of compressed transmission data nodes. On the basis of the characteristics of leaf node attack behavior, the fuzzy consistent judgment matrix is constructed to determine the weight of each security attribute of leaf node, calculate the probability of attack leaf node, and complete the intrusion detection of compressed transmission data node according to the calculation results. The experimental results show that the proposed method has high clustering accuracy, high detection efficiency and high detection accuracy. The shortest detection time is only 2.7 s, and the highest detection accuracy is 98.9%.