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Network traffic anomaly detection method and device

An anomaly detection and network traffic technology, applied in the field of information security, can solve problems such as low detection efficiency and accuracy of network traffic anomaly detection, and achieve the effects of reducing data volume, high accuracy, and improving detection efficiency

Active Publication Date: 2018-12-21
成都亚信网络安全产业技术研究院有限公司
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  • Application Information

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Problems solved by technology

[0005] Embodiments of the present invention provide a method and device for detecting network traffic anomalies, which are used to solve the problem of low detection accuracy and low detection efficiency of network traffic anomalies in the prior art

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  • Network traffic anomaly detection method and device
  • Network traffic anomaly detection method and device

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Embodiment Construction

[0054] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the scope of protection of this application. The use of the terms "first" and "second" etc. does not denote any order, and the above terms may be interpreted as names of the described objects. In the embodiments of the present application, words such as "exemplary" or "for example" are used as examples, illustrations or illustrations. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of the present application shall not be interpreted as being more preferred or more advanta...

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Abstract

The invention provides a network traffic anomaly detection method and device, which relate to the technical field of information security and are used for solving the problem of low accuracy and efficiency of network traffic anomaly detection. The method comprises the following steps of: analyzing network traffic anomaly detection samples by using a preset clustering analysis algorithm and obtaining the distribution characteristics of data points for clustering analysis; eliminating dense data points in the clustering analysis result to obtain a preliminary anomaly detection data set; A presetclustering algorithm addinga referrer field to each data point to point the data point to the nearest neighboring data point;according to the preset outlier analysis algorithm, obtaining the first outlier set and the outlier number of the preliminary outlier detection data set, and adjusting the distance parameter value according to the preset outlier analysis algorithm, the number of outlier points and the number of local outlier factors to obtain a second outlier set, and taking the intersection of the first outlier set and the second outlier set as the network traffic anomaly detection result. The invention is used for detecting network traffic anomaly.

Description

[0001] technology neighborhood [0002] The present invention relates to the technical field of information security, in particular to a method and device for detecting network traffic anomalies. Background technique [0003] Abnormal network traffic refers to the situation where the traffic behavior of the network deviates from the normal behavior, for example, there is a sudden abnormal major change in the network traffic. There are many reasons for abnormal network traffic, such as abnormal network equipment, abnormal network operation, abnormal flash congestion, network attack behavior, etc. Abnormal network traffic not only affects the normal use of the network and business systems, but also threatens the information security of network users, causing many harms to network users. [0004] At present, the network traffic anomaly detection method involving unsupervised learning in machine learning is usually implemented by cluster analysis algorithm and outlier analysis al...

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Application Information

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IPC IPC(8): H04L29/06
CPCH04L63/1416H04L63/1425
Inventor 郭栋
Owner 成都亚信网络安全产业技术研究院有限公司
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