Promising Techniques for Anomaly Detection on Network Traffic

Hui Tian1, 2, Jingtian Liu1 and Meimei Ding1

  1. School of Electronics and Information Engineering
    Beijing Jiaotong Univeristy
  2. School of Computer Science
    University of Adelaide

Abstract

In various networks, anomaly may happen due to network breakdown, intrusion detection, and end-to-end traffic changes. To detect these anomalies is important in diagnosis, fault report, capacity plan and so on. However, it’s challenging to detect these anomalies with high accuracy rate and time efficiency. Existing works are mainly classified into two streams, anomaly detection on link traffic and on global traffic. In this paper we discuss various anomaly detection methods on both types of traffic and compare their performance.

Key words

diffusion wavelet, principal component analysis, anomaly detection

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS170201018H

Publication information

Volume 14, Issue 3 (September 2017)
Advances in Information Technology, Distributed and Model Driven Systems
Year of Publication: 2017
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

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How to cite

Tian, H., Liu, J., Ding, M.: Promising Techniques for Anomaly Detection on Network Traffic. Computer Science and Information Systems, Vol. 14, No. 3, 597–609. (2017)