Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/112071
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Tian, H. | - |
dc.contributor.author | Liu, J. | - |
dc.contributor.author | Ding, M. | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Computer Science and Information Systems, 2017; 14(3):597-609 | - |
dc.identifier.issn | 1820-0214 | - |
dc.identifier.issn | 2406-1018 | - |
dc.identifier.uri | http://hdl.handle.net/2440/112071 | - |
dc.description.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. | - |
dc.description.statementofresponsibility | Hui Tian, Jingtian Liu and Meimei Ding | - |
dc.language.iso | en | - |
dc.publisher | ComSIS Consortium | - |
dc.rights | Computer Science and Information Systems is an Open Access journal. All articles can be downloaded free of charge and used in accordance with the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY NC ND) License. | - |
dc.source.uri | http://dx.doi.org/10.2298/csis170201018h | - |
dc.subject | Diffusion wavelet; principal component analysis; anomaly detection | - |
dc.title | Promising techniques for anomaly detection on network traffic | - |
dc.type | Journal article | - |
dc.identifier.doi | 10.2298/CSIS170201018H | - |
dc.relation.grant | http://purl.org/au-research/grants/arc/DP150104871 | - |
pubs.publication-status | Published | - |
Appears in Collections: | Aurora harvest 8 Computer Science publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
hdl_112071.pdf | Published Version | 616.12 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.