Feature adaptive reinforcement learning DDoS attack elimination method and system

Abstract

The embodiment of the invention discloses a feature adaptive reinforcement learning DDoS attack elimination method and a feature adaptive reinforcement learning DDoS attack elimination system. According to the collected historical data information, a better simplified feature subset is extracted; a reinforcement learning model is established according to a potential and predictable traffic flow space-time rule in the Internet of Vehicles; and a Q-learning agent is trained according to the reinforcement learning model to select a feature suitable for the current DDoS attack type, and meanwhile,a DDQN agent is asynchronously trained to obtain a strategy pi DDQN (st) to guide the selection of the Q-learning agent action. According to the method, the purpose of detecting the unknown type of DDoS attack in the Internet of Vehicles is achieved with a small amount of priori knowledge by adaptively learning attack features, dependence on labeled data is gotten rid of, and therefore the DDoS attack elimination method is obtained, and the requirements for low time delay and high accuracy in the Internet of Vehicles are met.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of Internet of Vehicles, and in particular to a method and system for eliminating DDoS attacks through feature-adaptive reinforcement learning. Background technique [0002] With the development of 5G technology, Mobile Edge Computing (MEC, Mobile Edge Computing) technology is introduced into the Internet of Vehicles to meet the needs of real-time data processing. Here, each base station serves as a MEC service station, which can reduce information forwarding time and Additional network operations, but this also makes the base station vulnerable to DDoS (Distributed denial of service attack) attacks initiated by vehicles. These DDoS attackers can send data far greater than the processing capacity of the MEC service station, exhausting the MEC service The resources of the base station will cause a denial of service. At this time, normal vehicles will not be able to establish a normal con...

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Problems solved by technology

[0004] For this reason, the embodiment of the present invention provides a method and system for eliminating DDoS attacks by feature-adaptive reinforcement learning to solve the existing DDoS attack detection methods in the Internet of Vehicles environment, which are restricted by prior knowledge, have large delays, and detect low accuracy problem

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