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

A technology of wireless local area network and deep learning, applied in the field of wireless local area network intrusion detection, can solve the problem that there is no effective system for wireless sensor network intrusion detection, achieve the effect of increasing the processing granularity, increasing the amount of information, and reducing the rate of misjudgment

Active Publication Date: 2019-04-30
CHONGQING UNIV OF POSTS & TELECOMM
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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, an

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

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Embodiment Construction

[0028] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0029] Such as figure 1 As shown, the present embodiment provides a wireless local area network intrusion detection system based on deep learning, the system includes: data collection module 10, RNN learning module 20, RNN verification module 30, acquisition preprocessing module 40, RNN identification module 50, The result processing module 60, wherein the data collection module is responsible for collecting wireless local area network data as a sample, and constructs and divides the data set, the RNN learning module reads the constructed and divided data set and performs model and parameter learning to build an acquired model, and the RNN verification module The acquired model is verified and tested, the verification data comes from the data collection module, and the results are fed back to the RNN learning module to optimize the test results; the col...

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Abstract

The invention discloses a wireless local area network intrusion detection system based on deep learning, and relates to the field of network space security. The system comprises model learning and intrusion detection, the model learning is responsible for pre-constructing an RNN neural network, and intrusion detection uses the constructed RNN neural network to complete an intrusion detection taskin real time. An LSTM recurrent neural network is adopted to carry out classification prediction on data traffic of a wireless local area network with a time sequence characteristic; the type of the target network traffic sequence is judged according to the output predicted by the identification module; The intrusion behavior in the target network is identified, different granularity processing isperformed according to the set priorities and processing methods, early warning and prevention are performed on possible information security problems, the confidentiality, the usability and the integrity of the wireless local area network are guaranteed, and the security level of the wireless local area network is improved.

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, ...

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Application Information

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IPC IPC(8): H04L29/06H04L12/24
CPCH04L41/142H04L41/145H04L41/147H04L63/1416H04L63/1441
Inventor 程克非张航
Owner CHONGQING UNIV OF POSTS & TELECOMM
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