A Ldos Attack Detection Method Based on Frequency Domain Feature Fusion

Abstract

The invention discloses an LDoS attack detection method based on frequency domain feature fusion, which belongs to the field of computer network security. The method includes: firstly, obtaining the network data message in the router to obtain the sample sequence; then, based on discrete Fourier transform and discrete wavelet transform, transforming the sample sequence from the time domain to the frequency domain, fully extracting the sample sequence Frequency-domain features; then, linear discriminant analysis is used to fuse the extracted frequency-domain features to obtain decision features, which can significantly improve the classification performance of features; finally, input the decision features into the pre-trained single-class classification anomaly detection model, And according to the output of the anomaly detection model, the network data packets in the unit time are judged and detected. If the output of the anomaly detection model is -1, it is determined that an LDoS attack has occurred in the network in the unit time. The detection method based on frequency domain feature fusion proposed by the invention can efficiently, quickly and accurately detect LDoS attacks.

Description

technical field [0001] The invention belongs to the field of computer network security, and in particular relates to an LDoS attack detection method based on frequency domain feature fusion. Background technique [0002] Denial of Service (DoS) attack is an attack that damages service availability. The attack attempts to exhaust some important resources related to the service, thereby hindering some normal services provided by the victim system and destroying service availability. DoS attacks do great harm to the network. With the development of DoS attack-related technologies, attack methods and means are becoming more and more diverse and intelligent. The Low-rate Denial of Service (LDoS) attack is a DoS attack variant that has appeared in recent years. Compared with traditional DoS attacks, LDoS attacks are not only more destructive, but also more concealable. [0003] At present, there are two problems in LDoS attack detection: one is that due to the low rate and stro...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the shortcomings of the existing LDoS attack detection methods, such as low detection accuracy and large resource consumption, an LDoS attack detection method based on frequency domain feature fusion is proposed.

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