Anomaly Detection Technology of Intelligent Networked Vehicle CAN Bus Based on Feature Information Entropy and Support Vector Machine
Based on the structural characteristics of CNA messages,this paper explores the anomaly detec-tion technology based on feature and information entropy and the anomaly detection technology based on sup-port vector machine.The anomaly detection technology based on feature and information entropy takes CAN ID as a feature,collects statistics on all packets containing the feature,and calculates the information en-tropy.Establish a threshold standard based on information entropy,and compare the entropy of CAN bus packets to check whether the entropy is within the threshold range.Simulation results show that the anomaly detection rate of this technology can reach 100％when the number of packets is small.Based on the support vector machine(SVM)anomaly detection technology,the abnormal message is preprocessed and input into SVM for training,and the anomaly detection index is obtained.The indicator is compared with the CAN bus message to detect whether there is an exception.The experimental results show that the anomaly detection rate of various CNA messages is more than 90％.
information entropysupport vector machineCAN busanomaly detection
万方数据
维普
