A perceptual intrusion detection method based on qsfla-svm

Abstract

The invention provides a perceptual intrusion detection method of QSFLA-SVM, which sets relevant parameters; initializes the position of the frog population; transfers the position information of each frog individual into a support vector machine abnormal sequence detection model, and uses the calculated test set The classification accuracy is used as the fitness function value of each frog individual, and the frog population is sorted in descending order and the sub-population is divided into sub-populations; the worst individual of each frog sub-population is updated by using the quantum particle swarm update mechanism until reaching Local maximum number of iterations; global information exchange is performed. If the global maximum number of iterations is reached, the global optimal frog individual will be returned. At this time, the location information of the individual is the optimal value of the parameter when the SVM anomaly sequence detection model obtains the maximum accuracy rate for the classification of the test set. , and output the optimal test set classification result. The invention combines a quantum-derived hybrid leapfrog intrusion detection algorithm based on a quantum particle swarm search mechanism and a support vector machine to perform intrusion detection.

Description

technical field [0001] The invention relates to a perceptual intrusion detection method of QSFLA-SVM, which belongs to the technical field of intrusion detection. Background technique [0002] In recent years, APT attacks have swept the world. Since the industrial control system has serious security problems and is related to the country's economic development and industrial construction, it is easy to become the target of the attack. Production suffered serious losses. Intrusion detection is an important subject in the field of industrial control, and its detection effect directly affects the security of the entire industrial control system. The perceptual intrusion detection model based on QSFLA-SVM is a method for identifying abnormal sequences and behaviors of intrusion detection systems. Therefore, scholars at home and abroad have conducted in-depth research on intrusion detection and achieved important results. [0003] The methods with good effect in the existing l...

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

Images