Security Protection Technology in Multi-Attribute Data Transmission Based on Fuzzy Genetic Algorithm

Abstract

Because the traditional data transmission security protection methods ignore the process of multi-attribute data detection, resulting in the abnormal data false alarm rate, high missing alarm rate, eliminating accuracy and other problems, a multi-attribute data transmission security protection method based on fuzzy genetic algorithm is proposed. The anomaly detection method based on fuzzy data mining and genetic algorithm is adopted to detect and obtain the abnormal data in the multi-attribute data transmission, and the abnormal data in the multi-attribute data transmission is eliminated through the abnormal data elimination method based on PSO and SVM, so as to realize the security protection of multi-attribute data transmission. It is verified that the recall rate and accuracy rate of abnormal data of the proposed method are higher than 95%, and the removal accuracy of abnormal data is higher. Moreover, this method is far better than the comparison method in positive likelihood ratio and Jordan index, and has higher application value.