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...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Harbin University of Science and Technology Publications
2019-08-01
|
| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1718 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849760898648899584 |
|---|---|
| author | XU Hong-jun ZHANG Hong HE Wei |
| author_facet | XU Hong-jun ZHANG Hong HE Wei |
| author_sort | XU Hong-jun |
| collection | DOAJ |
| description |
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. |
| format | Article |
| id | doaj-art-3f03b7303e47409ca2d520edf06b89f6 |
| institution | DOAJ |
| issn | 1007-2683 |
| language | zho |
| publishDate | 2019-08-01 |
| publisher | Harbin University of Science and Technology Publications |
| record_format | Article |
| series | Journal of Harbin University of Science and Technology |
| spelling | doaj-art-3f03b7303e47409ca2d520edf06b89f62025-08-20T03:06:13ZzhoHarbin University of Science and Technology PublicationsJournal of Harbin University of Science and Technology1007-26832019-08-01240412713210.15938/j.jhust.2019.04.021A Cloud User Anomaly Detection Method Based on Mouse BehaviorXU Hong-jun0ZHANG Hong1HE Wei2School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080,China;School of Information, Heilongjiang Agricultural Engineering Vocational College, Harbin 150088,ChinaSchool of Information, Heilongjiang Agricultural Engineering Vocational College, Harbin 150088,ChinaSchool of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025,China 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.https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1718cloud securitydepth learningconvolutional neural network（cnn）operational behaviorabnormal behavior detection |
| spellingShingle | XU Hong-jun ZHANG Hong HE Wei A Cloud User Anomaly Detection Method Based on Mouse Behavior Journal of Harbin University of Science and Technology cloud security depth learning convolutional neural network（cnn） operational behavior abnormal behavior detection |
| title | A Cloud User Anomaly Detection Method Based on Mouse Behavior |
| title_full | A Cloud User Anomaly Detection Method Based on Mouse Behavior |
| title_fullStr | A Cloud User Anomaly Detection Method Based on Mouse Behavior |
| title_full_unstemmed | A Cloud User Anomaly Detection Method Based on Mouse Behavior |
| title_short | A Cloud User Anomaly Detection Method Based on Mouse Behavior |
| title_sort | cloud user anomaly detection method based on mouse behavior |
| topic | cloud security depth learning convolutional neural network（cnn） operational behavior abnormal behavior detection |
| url | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1718 |
| work_keys_str_mv | AT xuhongjun aclouduseranomalydetectionmethodbasedonmousebehavior AT zhanghong aclouduseranomalydetectionmethodbasedonmousebehavior AT hewei aclouduseranomalydetectionmethodbasedonmousebehavior AT xuhongjun clouduseranomalydetectionmethodbasedonmousebehavior AT zhanghong clouduseranomalydetectionmethodbasedonmousebehavior AT hewei clouduseranomalydetectionmethodbasedonmousebehavior |