CAN Bus Intrusion Detection Algorithm Based on Annealing Optimization Window
Conventional Controller Area Network(CAN)lacks built-in security modules,which makes it easy for attackers to access in-vehicle network broadcasting information.To eliminate this threat,a variety of intrusion detection methods have been proposed.Machine learning methods are widely recognized as useful,but applying such methods in the vehicle requires processors with powerful computing power and high cost.In order to achieve real-time intrusion detection in in-vehicle net-works,a sliding-window based information entropy monitoring algorithm is now utilized,which is de-ployed on the CAN bus network nodes through less computational effort,and the size of the sliding win-dow can be optimized by a simulated annealing algorithm.Taking the DoS attack as an example,this method can detect the occurrence of the attack behavior in real time by the information entropy anoma-ly.
controller local area networkintrusion detectionDoS attackin-vehicle information security
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维普
