A trajectory-based abnormal behavior detection method and device
A detection method and abnormal technology, applied in the field of network security, can solve problems such as inaccurate detection results and large amount of calculation
Active Publication Date: 2019-05-07
WUHAN JIYI NETWORK TECH CO LTD
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[0005] In order to overcome the above-mentioned problems of inaccurate detection results and large amount of calculation in the existing trajectory-based abnormal behavior detection method, or at least partially solve the above problems, an embodiment of the present invention provides a trajectory-based abnormal behavior detection method and device
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[0025] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.
[0026] In one embodiment of the present invention, a trajectory-based abnormal behavior detection method is provided, figure 1 It is a schematic diagram of the overall flow of the track-based abnormal behavior detection method provided by the embodiment of the present invention, the method includes: S101, from the track data to be detected and the...
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The embodiment of the invention provides a trajectory-based abnormal behavior detection method and device. The method comprises: extracting multi-dimensional feature data from to-be-detected track data and historical track data in a preset time window before the to-be-detected track data are generated, and carrying out PCA orthogonal transformation on the feature data of the to-be-detected track data and the feature data of the historical track data; Dividing all the dimensional feature data after PCA orthogonal transformation of all the historical track data into a plurality of groups according to preset segmentation points, and calculating the average quantity of all the dimensional feature data of all the historical track data in each group; And according to a preset segmentation point,obtaining a group to which the feature data of each dimension of the to-be-detected track data belong, comparing the number of the feature data in the group to which the feature data of each dimension of the to-be-detected track data belong with an average number corresponding to the feature data of each dimension, and determining whether an abnormal behavior exists according to a comparison result. The embodiment of the invention is high in calculation efficiency and accurate in detection.
Description
technical field [0001] Embodiments of the present invention belong to the technical field of network security, and more specifically, relate to a method and device for detecting abnormal behaviors based on traces. Background technique [0002] In the field of verification security, trajectory-based abnormal behavior detection is one of the basic dimensions of security detection. Some hackers use scripts to forge a large amount of trajectory data to bypass verification. These batch trajectories are not exactly the same, but slightly change the trajectory coordinates. For this attack mode, an unsupervised clustering model is generally used to identify similar behavior trajectories, which can aggregate similar data together according to the characteristics of the data itself to the greatest extent. [0003] At present, the commonly used trajectory clustering methods mainly include: (1) distance-based trajectory clustering method, which mainly determines the similarity between ...
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IPC IPC(8): G06K9/62
Inventor 刘忠雨胡一然陈国庆
Owner WUHAN JIYI NETWORK TECH CO LTD