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Method, apparatus and system for detecting abnormal user behavior

A detection method and behavioral technology, applied in transmission systems, digital transmission systems, computer security devices, etc., can solve problems such as slow detection speed, inaccurate detection, and complicated abnormal judgment process, and achieve the effect of simplifying the judgment process and accurate detection

Inactive Publication Date: 2018-11-13
中国移动通信集团重庆有限公司 +2
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  • Claims
  • Application Information

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Problems solved by technology

[0005] In order to solve the problems that the current abnormal user behavior detection method based on clustering is complex in judging the abnormal process, and has the problems of slow detection speed and inaccurate detection, the embodiment of the present invention provides a method, device and system for detecting abnormal user behavior

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  • Method, apparatus and system for detecting abnormal user behavior
  • Method, apparatus and system for detecting abnormal user behavior
  • Method, apparatus and system for detecting abnormal user behavior

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Embodiment Construction

[0058] Features and exemplary embodiments of various aspects of the invention will be described in detail below. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced without some of these specific details. The following description of the embodiments is only to provide a better understanding of the present invention by showing examples of the present invention. The present invention is by no means limited to any specific configurations and algorithms presented below, but covers any modification, substitution and improvement of elements, components and algorithms without departing from the spirit of the invention. In the drawings and the following description, well-known structures and techniques have not been shown in order to avoid unnecessarily obscuring the present invention.

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Abstract

The invention provides a method, apparatus and system for detecting an abnormal user behavior. The method for detecting the abnormal user behavior comprises the following steps: obtaining user behavior information; extracting user behavior feature values related to user behaviors from the user behavior information; calculating a clustering centroid of the user behavior feature values related to each type of user behaviors according to the clustering characteristics of the user behavior feature values; determining a standard baseline of a normal user behavior by using the clustering centroid as the center; calculating the distance between the user behavior feature values of the user behavior information and the clustering centroid; and comparing the calculated distances with the standard baseline to judge whether the user behavior information belongs to abnormal behavior information. According to the method provided by the invention, by collecting the user behavior information, extracting the feature values from the user behavior information, and performing clustering analysis on the extracted feature values in combination with the normal behavior standard baseline to judge the abnormal situation of the user behaviors, thereby simplifying the judgment process of the abnormal user behavior and realizing fast and accurate detection of the abnormal user behavior.

Description

technical field [0001] The invention relates to the technical field of network user behavior monitoring, and specifically designs a method and system for detecting abnormal user behavior. Background technique [0002] With the popularization and development of computers and networks, whether it is a local area network or a wide area network, the scale of network users is gradually expanding, and user behaviors are becoming more and more complex. In this context, rapid detection and effective control of user behavior is particularly important. . Clustering is a process of classifying data into different classes or clusters, so objects in the same cluster have great similarity, while objects in different clusters have great dissimilarity. The goal of cluster analysis is that the objects in a group are related to each other, while the objects in different groups are not related. The greater the similarity within groups and the greater the differences between groups, the bette...

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Application Information

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IPC IPC(8): H04L12/26H04L12/24G06F17/30
CPCG06F21/554G06F21/566H04L41/14H04L43/10H04L43/16
Inventor 赵立农陆艳军陈浪杨翔邓秘密黄国强廖天宇
Owner 中国移动通信集团重庆有限公司
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