A method and system for intrusion attack detection of Internet of Vehicles based on artificial intelligence behavior analysis

Abstract

The invention relates to the field of network technology, and discloses a vehicle network intrusion attack detection method and system based on artificial intelligence behavior analysis. The method includes: obtaining Internet traffic data, restoring the traffic according to the communication protocol, and obtaining an online bill log; at least filtering the above bill log according to one or more characteristics of APN, number segment, and Internet of Vehicles APP; using From the known normal access data and abnormal intrusion attack data of the Internet of Vehicles, extract the access parameter features and access behavior features, and use the artificial intelligence classifier model for training; extract the access parameter features and access behavior features from the real-time Internet of Vehicles access data, Use the trained classifier model to judge whether an intrusion attack has been encountered, and deal with the intrusion attack behavior accordingly. The method and system of the present invention can accurately judge whether external behaviors intrude on networked vehicles.

Description

technical field [0001] The invention relates to the field of network technology, and in particular, to a method and system for detecting intrusion attacks in the Internet of Vehicles based on artificial intelligence behavior analysis. Background technique [0002] According to the data of the "Intelligent and Connected Vehicle Information Security White Paper" released by the China Association of Automotive Engineers in 2017, the penetration rate of intelligent driving passenger vehicles in China reached 15% in 2015, and this figure is expected to reach 50% in 2019. ICVs generally communicate with on-board sensor networks, on-board smart terminals, cloud TSPs, and car owners’ mobile APPs through the mobile network, and the communication data is transmitted through the public network, which also gives hackers an opportunity. Infiltrate, invade, attack, to achieve illegal purposes. [0003] The hidden dangers of network security exist in each component of the Internet of Vehi...

AI Technical Summary

Problems solved by technology

[0003] Hidden dangers of network security exist in all components of the Internet of Vehicles architecture. The network security protection of the Internet of Vehicles needs to be implemented through multiple layers of the cloud pipe end. Since the data of the Internet of Vehicles is usually transmitted in an encrypted manner, it is generally impossible to identify and analyze it on the pipe side of the mobile network The plaintext of the Internet of Vehicles data, the traditional intrusion detection method cannot judge the legality of the data

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