Network-Wide Traffic Anomaly Detection and Localization Based on Robust Multivariate Probabilistic Calibration Model
Joint Authors
Li, Yuchong
Luo, Xingguo
Qian, Yekui
Zhao, Xin
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-26, 26 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-08-31
Country of Publication
Egypt
No. of Pages
26
Main Subjects
Abstract EN
Network anomaly detection and localization are of great significance to network security.
Compared with the traditional methods of host computer, single link and single path, the network-wide anomaly detection approaches have distinctive advantages with respect to detection precision and range.
However, when facing the actual problems of noise interference or data loss, the network-wide anomaly detection approaches also suffer significant performance reduction or may even become unavailable.
Besides, researches on anomaly localization are rare.
In order to solve the mentioned problems, this paper presents a robust multivariate probabilistic calibration model for network-wide anomaly detection and localization.
It applies the latent variable probability theory with multivariate t-distribution to establish the normal traffic model.
Not only does the algorithm implement network anomaly detection by judging whether the sample’s Mahalanobis distance exceeds the threshold, but also it locates anomalies by contribution analysis.
Both theoretical analysis and experimental results demonstrate its robustness and wider use.
The algorithm is applicable when dealing with both data integrity and loss.
It also has a stronger resistance over noise interference and lower sensitivity to the change of parameters, all of which indicate its performance stability.
American Psychological Association (APA)
Li, Yuchong& Luo, Xingguo& Qian, Yekui& Zhao, Xin. 2015. Network-Wide Traffic Anomaly Detection and Localization Based on Robust Multivariate Probabilistic Calibration Model. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-26.
https://search.emarefa.net/detail/BIM-1075075
Modern Language Association (MLA)
Li, Yuchong…[et al.]. Network-Wide Traffic Anomaly Detection and Localization Based on Robust Multivariate Probabilistic Calibration Model. Mathematical Problems in Engineering No. 2015 (2015), pp.1-26.
https://search.emarefa.net/detail/BIM-1075075
American Medical Association (AMA)
Li, Yuchong& Luo, Xingguo& Qian, Yekui& Zhao, Xin. Network-Wide Traffic Anomaly Detection and Localization Based on Robust Multivariate Probabilistic Calibration Model. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-26.
https://search.emarefa.net/detail/BIM-1075075
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1075075