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Abnormal behavior detection method and system based on big-data association rule mining

A detection method and correlation technology, applied in the computer field, can solve the problems of missed detection and high error rate, and achieve the effect of improving accuracy and high accuracy rate

Active Publication Date: 2016-08-10
SOUTH CHINA NORMAL UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, normal behavior may be misdetected as abnormal behavior, and abnormal behavior may be missed as normal behavior, resulting in a high error rate for abnormal behavior detection

Method used

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  • Abnormal behavior detection method and system based on big-data association rule mining
  • Abnormal behavior detection method and system based on big-data association rule mining
  • Abnormal behavior detection method and system based on big-data association rule mining

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Experimental program
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Embodiment Construction

[0051] In one embodiment, such as figure 1 As shown, an abnormal behavior detection method is proposed, which includes the following steps:

[0052] Step 102, acquiring the user's behavior information to be detected, and calculating the matching degree between the behavior information to be detected and the historical abnormal behavior information stored in the user behavior database in advance.

[0053] In this embodiment, a user is a single individual. The behavior information to be detected is a specific behavior information of the user. For example, the behavior information to be detected of the user can be the behavior sequence of the user withdrawing money from the ATM machine "walk into the bank -> insert the card -> enter the password -> withdraw money - >Walking out of the bank” any behavior action information, such as withdrawal.

[0054] The user's behavior information to be detected can be the operation information performed by the user when shopping on a shopping ...

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Abstract

The invention relates to an abnormal behavior detection method and system. The method comprises steps as follows: acquiring to-be-detected behavior information of a user, and calculating the matching degree between the to-be-detected behavior information and historical abnormal behavior information; screening out the historical abnormal behavior information with the matching degree higher than a first preset threshold; acquiring an abnormal behavior sequence corresponding to the screened-out historical abnormal behavior information, and acquiring an association relationship between the screened-out historical abnormal behavior information and association behavior information corresponding to the historical abnormal behavior information in the abnormal behavior sequence; acquiring the association behavior information of the to-be-detected behavior information according to the association relationship, and constituting a to-be-detected behavior sequence by the to-be-detected behavior information and the association behavior information corresponding to the to-be-detected behavior information; calculating similarity of the to-be-detected behavior sequence and the abnormal behavior sequence; acquiring to-be-detected behavior information with the similarity higher than a second preset threshold, and determining the acquired to-be-detected behavior information as abnormal behavior information. According to the abnormal behavior detection method and system, abnormal behavior detection for the user can be performed accurately.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to an abnormal behavior detection method and system based on big data association rule mining. Background technique [0002] Abnormal user behavior often refers to "abnormal" behavior that violates social civilization norms or group behavior habits and standards. Especially with the improvement of people's awareness of public security and network security, people pay more and more attention to abnormal behavior detection in crowd scenes, networks and other environments. [0003] At present, the detection of abnormal behavior of users usually performs matching detection based on the characteristics of individual abnormal behaviors, or performs comparative detection based on the characteristics of individual normal behaviors. But since the same behavior may be abnormal in some cases and normal in others. Therefore, normal behaviors may be misdetected as abnormal behaviors, and abn...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/219G06F16/24553G06F16/24564G06F16/2462G06F16/2465G06F16/2468
Inventor 朱定局
Owner SOUTH CHINA NORMAL UNIVERSITY
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