Internet of vehicles intrusion detection method and system based on deep reinforcement learning

Abstract

The invention discloses an Internet of Vehicles intrusion detection method and system based on deep reinforcement learning. The method comprises the following steps: calculating statistical characteristics of traffic data at historical moments; establishing a flow prediction model based on a deep reinforcement learning algorithm-a deep deterministic strategy gradient algorithm; wherein the input of the flow prediction model is the statistical characteristics, and the output of the flow prediction model is predicted flow; establishing an intrusion detection model based on a depth deterministic strategy gradient algorithm; wherein the input of the intrusion detection model is the statistical characteristics and the predicted traffic, and the output of the intrusion detection model is a traffic threshold; and performing Internet of Vehicles intrusion detection by comparing the predicted traffic with the traffic threshold. According to the method, the complexity variability of the Internet of Vehicles, the finiteness of computing resources of the infrastructure server side and the accuracy of network intrusion detection can be considered, and the method is more practical. For a complex system of the Internet of Vehicles, the intrusion detection method based on deep reinforcement learning provided by the invention has better performance compared with other existing multipurpose methods.

Description

technical field [0001] The invention relates to the technical field of network security, in particular to a vehicle network intrusion detection method and system based on deep reinforcement learning. Background technique [0002] With the continuous development and successful application of communication network technology, people have put forward higher requirements for Internet of Vehicles services, which directly leads to the increasingly complex structure of Internet of Vehicles. With the increasing complexity and connectivity of modern vehicles, the network security risks of the Internet of Vehicles are becoming more and more prominent. In order to ensure the security and normal operation of the network, real-time and reliable security enhancement methods are essential. As a lightweight security enhancement method, the intrusion detection system can well detect internal and external threats to the network, and has good cost-effectiveness and high compatibility. It is c...

AI Technical Summary

Problems solved by technology

[0004] Although many methods have been proposed to improve the accuracy of intrusion detection, a significant problem is that it is difficult to select effective features to model normal behavior.

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