A Data Mining Method Using Deep Learning for Anomaly Detection in Cloud Computing Environment
Joint Authors
Gao, Jin
Zhang, Qi
Wang, Xinyang
Liu, Jiaquan
Guo, Sihua
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-11-20
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Aiming at problems such as slow training speed, poor prediction effect, and unstable detection results of traditional anomaly detection algorithms, a data mining method for anomaly detection based on the deep variational dimensionality reduction model and MapReduce (DMAD-DVDMR) in cloud computing environment is proposed.
First of all, the data are preprocessed by a dimensionality reduction model based on deep variational learning and based on ensuring complete data information as much as possible, the dimensionality of the data is reduced, and the computational pressure is reduced.
Secondly, the data set stored on the Hadoop Distributed File System (HDFS) is logically divided into several data blocks, and the data blocks are processed in parallel through the principle of MapReduce, so the k-distance and LOF value of each data point can only be calculated in each block.
Thirdly, based on stochastic gradient descent, the concept of k-neighboring distance is redefined, thus avoiding the situation where there are greater than or equal to k-repeated points and infinite local density in the data set.
Finally, compared with CNN, DeepAnt, and SVM-IDS algorithms, the accuracy of the scheme is increased by 10.3%, 18.0%, and 17.2%, respectively.
The experimental data set verifies the effectiveness and scalability of the proposed DMAD-DVDMR algorithm.
American Psychological Association (APA)
Gao, Jin& Liu, Jiaquan& Guo, Sihua& Zhang, Qi& Wang, Xinyang. 2020. A Data Mining Method Using Deep Learning for Anomaly Detection in Cloud Computing Environment. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1196713
Modern Language Association (MLA)
Gao, Jin…[et al.]. A Data Mining Method Using Deep Learning for Anomaly Detection in Cloud Computing Environment. Mathematical Problems in Engineering No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1196713
American Medical Association (AMA)
Gao, Jin& Liu, Jiaquan& Guo, Sihua& Zhang, Qi& Wang, Xinyang. A Data Mining Method Using Deep Learning for Anomaly Detection in Cloud Computing Environment. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1196713
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1196713