A Cloud User Anomaly Detection Method Based on Mouse Behavior
Aiming at the problem of cloud security threat caused by illegal operation of cloud users, this paper proposes a method to detect the abnormal behavior of cloud users by analyzing the mouse operation behavior in user’s work by using deep learning technology under the premise of ensuring the priva...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Harbin University of Science and Technology Publications
2019-08-01
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| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1718 |
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| Summary: | Aiming at the problem of cloud security threat caused by illegal operation of cloud users, this paper proposes a method to detect the abnormal behavior of cloud users by analyzing the mouse operation behavior in user’s work by using deep learning technology under the premise of ensuring the privacy of cloud users. Firstly, the mouse track tool is used to record the trajectory of the user’s basic mouse operation within a certain period of time. Then, the convolution neural network is used to learn and classify the recorded trajectories. The experimental results show that the proposed method can effectively detect abnormal behavior of users under the precondition of ensuring user privacy, meanwhile, it can avoid the analysis and processing of high dimensional feature data and reduce the difficulty of abnormal behavior detection. |
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| ISSN: | 1007-2683 |