Detection method for abnormal behaviors based on user access sequence

A technology for accessing sequences and detection methods, applied in digital transmission systems, electrical components, transmission systems, etc., can solve the problems of inaccurate analysis results, low operation efficiency, and not well solved, and achieve accurate analysis results and operation. The effect of high efficiency and less use of resources

Active Publication Date: 2017-05-10
STATE GRID CORP OF CHINA +3
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Problems solved by technology

[0006] The above methods have certain limitations, such as how to define network traffic behavior, how to reduce the dimension of describing network behavior as much as possible, and how to effectively...

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  • Detection method for abnormal behaviors based on user access sequence
  • Detection method for abnormal behaviors based on user access sequence
  • Detection method for abnormal behaviors based on user access sequence

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[0040] The technical scheme of the present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments, so that those skilled in the art can better understand the present invention and implement it, but the examples given are not intended to limit the present invention.

[0041] Abnormal behavior detection methods based on user access sequences, such as figure 1 shown, including the following steps:

[0042] Step 1. Corresponding data preprocessing module: grab data from the local network, preprocess the data, and serialize the obtained data;

[0043] Step 2, corresponding sequence pattern mining module: store the sequence formed in step 1 into the sequence database, and generate the behavior sequence of each user based on time;

[0044] Step 3. Corresponding abnormal behavior detection module: Calculate the behavior similarity and correlation coefficient between users through the behavior sequence of each user, c...

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Abstract

The invention discloses a detection method for abnormal behaviors based on a user access sequence. The detection method comprises the following steps: 1) capturing data from a local network, preprocessing the data, and performing serializing treatment on the acquired data; 2) storing a sequence formed in the step 1 into a sequence database, and generating a behavior sequence of each user on the basis of time; and 3) calculating the behavior similarity and the correlation coefficient between users according to the behavior sequence of each user, comparing the correlation coefficient for detecting the abnormal behaviors, and searching for the abnormal behaviors of the user. According to the method, on the basis of sequence pattern excavation, factors, such as, time and user behavior characteristics, are fully considered, an improved more accurate user behavior similarity algorithm is utilized to calculate, and the sequence rule of the user access is effectively extracted, so that an analysis result is more accurate and the defects of other analysis methods are overcome. Besides, on the basis of the user behavior similarity algorithm, the method has obvious advantages in noise interference, the used resources are few, and the running efficiency is high.

Description

technical field [0001] The invention relates to an abnormal behavior detection method based on user access sequence. Background technique [0002] User behavior analysis refers to obtaining relevant network flow data from websites or network ports, and using statistical analysis methods to process the data. Through the obtained results, we can discover the rules of users visiting the website and summarize the behavior habits of users. Being able to grasp the user's behavior habits is of great significance for predicting the user's online behavior and discovering abnormal behavior. [0003] At present, various abnormal behavior detection algorithms are mainly divided into two categories: [0004] (1) The method based on data flow behavior analysis, the existing patents include: Patent No. 201110083016.X for network access anomaly detection device and method based on data flow behavior analysis, patent No. 201110371820.8 for network abnormal behavior detection method and dev...

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Application Information

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IPC IPC(8): H04L29/08H04L12/26
CPCH04L43/02H04L43/04H04L67/535
Inventor 廖鹏夏元轶郭靓于晓文金倩倩蒋甜张骞李炜键赵俊峰
Owner STATE GRID CORP OF CHINA
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