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Method for detecting abnormal user behaviours mined on the basis of variable-length sequence mode

A technology of pattern mining and detection methods, applied in the field of data analysis, it can solve the problems of offline analysis but cannot accurately describe the complex behavior of users, and achieve the effect of improving accuracy and real-time performance.

Active Publication Date: 2015-12-23
NAT UNIV OF DEFENSE TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] A user abnormal behavior detection method based on variable-length sequence pattern mining provided by the present invention can realize fast and efficient online detection of user abnormal behavior, and solve the problem that the existing technology can only be analyzed offline and cannot accurately describe complex behaviors of users

Method used

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  • Method for detecting abnormal user behaviours mined on the basis of variable-length sequence mode
  • Method for detecting abnormal user behaviours mined on the basis of variable-length sequence mode
  • Method for detecting abnormal user behaviours mined on the basis of variable-length sequence mode

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Embodiment 1

[0029] figure 1 It is a flow chart of an embodiment of the user abnormal behavior detection method based on variable-length sequence pattern mining provided by the present invention, as shown in figure 1 As shown, the method includes two stages, namely:

[0030] The first stage 1: the user's normal behavior training stage, this stage is mainly to use the user's historical behavior data modeling in the offline system to calculate the user's normal behavior pattern;

[0031] The second stage 2: user abnormal behavior detection stage, this stage is mainly to extract the user's current behavior pattern in the online system and match it with the normal behavior pattern in the database to see if the current behavior is abnormal.

[0032] Specifically, the normal user behavior training phase includes the following steps:

[0033] Step 11. Preprocessing the user’s normal behavior log data in the database to obtain multiple user normal behavior variable-length sequence streams; in th...

Embodiment 2

[0041] figure 2 The flow chart of Embodiment 2 of the abnormal user behavior detection method based on variable-length sequence pattern mining provided by the present invention, as shown in figure 2 As shown, on the basis of Embodiment 1, Embodiment 2 further includes:

[0042] Step 15, on the basis of constructing and generating the user's normal behavior pattern by each user's normal behavior variable-length sequence flow and the number of occurrences thereof, calculate the IDF (InverseDocumentFrequency) value of each user's normal behavior variable-length sequence flow, and according to the The IDF value updates the user's normal behavior pattern to obtain an optimized user's normal behavior pattern. The IDF value reflects the importance of a sequence. The higher the IDF value of a short sequence, the more important the sequence is to the user and the higher its recognition degree, that is, the current user can be distinguished from other users through this sequence; the...

Embodiment 3

[0044] image 3 The flow chart of Embodiment 3 of the abnormal user behavior detection method based on variable-length sequence pattern mining provided by the present invention, as shown in image 3 As shown, on the basis of the above-mentioned embodiments, this embodiment also includes:

[0045] Step 22: Calculate the IDF value of each variable-length sequence of user behavior to be detected, and if it is lower than the predetermined IDF threshold, delete the variable-length sequence of user behavior to omit the judgment of the variable-length sequence of user behavior. This step can screen many unnecessary tests and improve the detection efficiency. Furthermore, different predetermined IDF thresholds can be set correspondingly according to different sequence lengths in the user behavior variable-length sequence. When judging, when all the judgment values ​​are greater than the IDF value of its corresponding length, it is judged as the normal behavior of the user. Further p...

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Abstract

The invention provides a method for detecting abnormal user behaviours mined on the basis of a variable-length sequence mode. The method comprises a stage of training normal user behaviours and a stage of detecting abnormal user behaviours, wherein the stage of training the normal user behaviours comprises the following steps: (1), pre-processing normal user behaviour log data in a database so as to obtain a plurality of normal user behaviour variable-length sequence streams; and (2), constructing a mode for generating normal user behaviours according to each normal user behaviour variable-length sequence stream in the plurality of normal user behaviour variable-length sequence streams and the occurrence number of the normal user behaviour variable-length sequence stream; and the stage of detecting the abnormal user behaviours comprises the following steps: (1), generating a plurality of variable-length sequences based on user behaviour online data to be detected; and (2), matching and comparing the variable-length sequences with various variable-length sequence streams in the normal user behaviour mode so as to judge whether the user behaviour variable-length sequence to be detected is abnormal user behaviour data or not. By means of the method, online abnormal detection can be realized; and complex behaviours of users can be accurately described.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of data analysis, and in particular to a method for detecting user abnormal behavior based on variable-length sequence pattern mining. Background technique [0002] The rapid development of the Internet has given birth to the prosperity of e-commerce, among which the growth of virtual asset transactions is particularly rapid. At present, my country has carried out research on eID-based virtual asset management and preservation technology in cyberspace to achieve standardized and unified management of virtual assets. The virtual asset security system comprehensively and accurately records various operations on virtual assets, but how to dig out abnormal user transaction behaviors from these recorded data still faces many challenges. In view of the huge scale and very fast growth of network virtual asset transaction information, it is extremely urgent to automatically discover and pr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L12/24
CPCH04L41/147
Inventor 朱伟辉傅翔贾焰韩伟红李树栋李爱平周斌杨树强黄九鸣李虎全拥邓璐
Owner NAT UNIV OF DEFENSE TECH
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