A deep learning-based wireless local area network intrusion detection method and system

Abstract

The invention discloses a wireless local area network intrusion detection system based on deep learning, which relates to the field of network space security. This system includes model learning and intrusion detection, in which model learning is responsible for pre-constructing the RNN neural network, and intrusion detection uses the constructed RNN neural network to complete the intrusion detection task in real time. The LSTM cycle neural network is used to classify and predict the data traffic of the wireless LAN network with time series characteristics, judge the category of the target network traffic sequence according to the output of the classification and prediction of the identification module, and identify the intrusion behavior in the target network, according to the set priority and processing Methods Different granularity processing is carried out to warn and prevent possible information security problems, to ensure the confidentiality, availability and integrity of the wireless local area network, and to improve the security level of the wireless local area network.

Description

technical field [0001] The invention relates to the technical field of network space security, in particular to a wireless local area network intrusion detection method and system. Background technique [0002] As a main application scenario of the Internet of Things, smart home devices have entered thousands of homes. In the field of smart homes, wireless communication technology is widely used for the interconnection of devices. The 802.11 series standards clearly stipulate that wireless local area networks (WLANs) The implementation on the media access control layer (MAC) and the physical layer (PHY) can provide basic and reliable wireless device interconnection for smart homes. The usual solution is to use a wireless router as a gateway to build a smart home that includes various smart home devices. WLANs form a star topology. By connecting smart home devices to the Internet, users can remotely view, control, and manage smart home devices at home at any time. However, ...

AI Technical Summary

Problems solved by technology

In 2018, a wireless sensor intrusion detection method based on deep learning (CN108234500A) disclosed an intrusion detection method that uses a deep belief network for feature learning, constructs a base classifier, and then uses a random forest algorithm to combine multiple classifiers. The method is mainly applicable to wireless sensor networks, and has not formed an effective system for wireless sensor network intrusion detection

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