User abnormal behavior detection method based on neural network clustering

A neural network and behavioral technology, applied in the field of information security credibility, can solve problems such as high false alarm rate, achieve the effect of improving decomposition speed and signal-to-noise ratio
CN105224872AActive Publication Date: 2016-01-06HENAN UNIV OF SCI & TECH
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
HENAN UNIV OF SCI & TECH
Publication Date
2016-01-06

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Abstract

The invention discloses a user abnormal behavior detection method based on neural network clustering. The method comprises: firstly, performing SVD decomposition and denoising on a behavior data set matrix of a user, and inputting the denoised matrix to an input layer of a neural network, and then calculating weight of all attributes of each user in a hidden layer of the neural network, and standardizing the weight, outputting the weight in an output layer, and finally respectively calculating similarity value of each user and each user in a normal behavior model database and a threshold value, if the similarity value is larger than the threshold value, behavior being abnormal behavior, and carrying out corresponding prompt and precautionary measures, otherwise, the behavior being normal behavior, and combining the behavior in the normal model database to upgrade the database in real time. Through cooperation of each part, the method effectively realizes high detection rate and low false alarm rate.
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Description

technical field

[0001] The invention relates to the technical field of information security credibility, in particular to a method for detecting user abnormal behavior based on neural network clustering. Background technique

[0002] Today is in the era of big data, all kinds of user information are stored in the computer, which brings convenience to people's work and life, but also makes information security face a severe test. With the popularization of computers, various hackers and intrusions emerge in endlessly , with the network attack technology becoming more mature and changing, the traditional passive defense methods obviously cannot solve the security problem of user information well. For various passive defense measures, people are more inclined to active detection technology, and adopt Graph clustering is a popular method for detecting abnormal user behavior.

[0003] Using the method of graph clustering to realize the identification and detection of user abnorm...

Claims

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