Security Analysis of Car Driving Identification System Based on Deep Learning

The implementation of the car driving identification system will help to improve the safety and efficiency of navigation. The safety analysis technology can filter the attack events of the automatic identification system of car driving and reduce the error rate of safety analysis. To this end, a deep learning-based safety analysis method for car driving identification system is proposed. Based on the deep learning theory, a safety behavior analysis model of the car driving identification system is constructed. Through data collection, security analysis and response processing, the identification of abnormal communication security data strength is completed. A Cartesian coordinate system is established, and a heterogeneous data processing model is constructed. Based on the deep learning analysis process of security data, based on deep learning, by accessing system operation data, stream processing and data mining of security data, complete system security data defense control, and realize system security analysis. The experimental results show that the method in this paper has strong security analysis ability, and its matching range is large, which can match all security behaviors and reduce the error rate of security analysis.