QSFLA-SVM-based perceptive intrusion detection method

Abstract

The invention provides a QSFLA-SVM-based perceptive intrusion detection method. The method comprises the steps of setting related parameters; initializing the position of a frog population; transmitting position information of each frog individual to an SVM abnormal sequence detection model, taking a calculated correct rate of test set classification as a fitness function value of each frog individual, performing descending order arrangement on the frog population and performing sub-population division on the arranged population; updating worst individuals of each frog sub-population by utilizing a quantum particle swarm update mechanism, until a local maximum iterative frequency is reached; and performing global information exchange, and if a global maximum iterative frequency is reached,returning a global optimal frog individual, and outputting an optimal test set classification result, wherein at the moment, position information of the global optimal frog individual is an optimal parameter value when the SVM abnormal sequence detection model obtains the maximum correct rate of the test set classification. According to the method, intrusion detection is performed in combinationwith a quantum particle swarm search mechanism-based QSFLA and an SVM.

Description

Technical field [0001] The invention relates to a QSFLA-SVM perceptual intrusion detection method, which belongs to the technical field of intrusion detection. Background technique [0002] In recent years, APT attacks have swept the world. Because industrial control systems have serious security problems and are related to the country’s economic development and industrial construction, they are easily targeted. Once they are attacked, the system cannot accurately identify abnormal situations, which will affect the industry. The production caused serious losses. Intrusion detection is an important subject in the field of industrial control, and its detection effect directly affects the safety of the entire industrial control system. The perceptual intrusion detection model based on QSFLA-SVM is a method to identify abnormal sequences and behaviors of intrusion detection systems. Therefore, scholars at home and abroad have conducted in-depth research on intrusion detection and a...

AI Technical Summary

Problems solved by technology

[0002] In recent years, APT attacks have swept the world. Since the industrial control system itself has serious security problems and is related to the country's economic development and industrial construction, it is easy to become the target of attacks. serious losses in production

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