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Abnormal traffic detection method and system based on DVAE-Catboost

A technology of abnormal traffic and detection method, which is applied in the direction of transmission system, neural learning method, biological neural network model, etc., can solve the problems of high-dimensional network traffic and large-scale data training difficulties, achieve broad application prospects, improve detection rate and detection Good accuracy and good scalability

Inactive Publication Date: 2020-08-11
FUZHOU UNIV
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Problems solved by technology

[0004] In view of this, the purpose of the present invention is to propose an abnormal traffic detection method and system based on DVAE-Catboost, which effectively solves the problem of dimensionality reduction of high-dimensional network traffic and difficult training of large batches of data in the process of abnormal traffic detection, and improves the detection efficiency. rate and detection accuracy

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  • Abnormal traffic detection method and system based on DVAE-Catboost
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  • Abnormal traffic detection method and system based on DVAE-Catboost

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Embodiment Construction

[0033] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0034] It should be pointed out that the following detailed description is exemplary and is intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0035] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combina...

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Abstract

The invention relates to an abnormal traffic detection method and system based on DVAE-Catboost. The method comprises the steps: collecting traffic data from a network link; extracting network trafficcharacteristics and then preprocessing the traffic data; employing a DVAE network for obtaining low-dimensional representation of high-dimensional network traffic data, and then employing a Catboostalgorithm for training an abnormal traffic detection model; finally, employing the trained abnormal traffic detection model for carrying out anomaly detection on real-time traffic, and carrying out the response processing.

Description

technical field [0001] The invention relates to the technical field of computer network security, in particular to a DVAE-Catboost-based abnormal flow detection method and system. Background technique [0002] As an effective method to realize network intrusion detection, network traffic anomaly detection can not only detect unknown network attacks, but also provide important support for network situational awareness. Abnormal network traffic has a great impact on the availability of the network, and even causes users to be unable to access the Internet normally. The main causes of abnormal network traffic are: first, network performance reasons, mainly referring to abnormal traffic caused by unreasonable network topology design or improper user operation, such as improper network policy settings by network administrators, network equipment failures, etc.; second, network security Reasons mainly refer to abnormal traffic caused by malicious network attacks, such as denial o...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L29/06G06N3/04G06N3/08G06N20/20
CPCH04L63/1425H04L63/1416G06N3/084G06N20/20G06N3/045
Inventor 张浩连鸿飞魏志强李杰铃陈龙
Owner FUZHOU UNIV