A network intrusion detection method based on meta-sample sparse representation

Abstract

The invention relates to the field of network security, and discloses a network intrusion detection method based on element sample sparse representation. The problems that a traditional common intrusion detection method is difficult to deal with unknown network attacks and the false alarm rate of anomaly detection is high are solved. The method comprises the steps that a, a network data collection tool is used to collect network instances to build a training sample set; b, an element sample is extracted from the built network training sample set in a centralized manner, and an element sample set is formed to replace the training sample set; and c, a sparse representation classification method is used to detect network data to be identified, so as to identify the category of the network data to be detected. The network intrusion detection method provided by the invention is applicable to network intrusion detection.

Description

technical field [0001] The invention relates to the field of network security, in particular to a network intrusion detection method based on sparse representation of meta samples. Background technique [0002] With the rapid development of network technology and the continuous expansion of network scale, network security problems are becoming more and more serious. As an important technology to maintain network security, intrusion detection has become an important research content in the field of information security, and has received extensive attention from many experts and scholars. Intrusion detection technology mainly judges whether there is any violation of system security or security policy in the system by analyzing relevant network data. [0003] Intrusion detection can be regarded as a classification problem in essence, and all behaviors in the network can be divided into two categories, namely normal behavior and abnormal behavior, so that intrusion detection ca...

AI Technical Summary

Problems solved by technology

[0007] The technical problem to be solved by the present invention is to propose a network intrusion detection method based on the sparse representation of meta-samples to solve the problems that the traditional commonly used intrusion detection methods are difficult to cope with unknown network attack behaviors and the false alarm rate of anomaly detection is too high

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