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Promising techniques for anomaly detection on network traffic
Author(s) -
Hui Tian,
Jingtian Liu,
Meimei Ding
Publication year - 2017
Publication title -
computer science and information systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.244
H-Index - 24
eISSN - 2406-1018
pISSN - 1820-0214
DOI - 10.2298/csis170201018h
Subject(s) - computer science , anomaly detection , anomaly (physics) , intrusion detection system , data mining , real time computing , artificial intelligence , physics , condensed matter physics
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.

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