Fine-grained traffic classification based on functional separation
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Byungchul | - |
dc.contributor.author | Won, Youngjoon | - |
dc.contributor.author | Chung, JaeYoon | - |
dc.contributor.author | Kim, Myung-sup | - |
dc.contributor.author | Hong, James Won-Ki | - |
dc.date.accessioned | 2021-09-05T22:00:24Z | - |
dc.date.available | 2021-09-05T22:00:24Z | - |
dc.date.created | 2021-06-14 | - |
dc.date.issued | 2013-09 | - |
dc.identifier.issn | 1055-7148 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/102230 | - |
dc.description.abstract | SUMMARY Current efforts to classify Internet traffic highlight accuracy. Previous studies have focused on the detection of major applications such as P2P and streaming applications. However, these applications can generate various types of traffic which are often considered as minor and ignorant traffic portions. As network applications become more complex, the price paid for not concentrating on minor traffic classes is in reduction of accuracy and completeness. In this context, we propose a fine-grained traffic classification scheme and its detailed method, called functional separation. Our proposal can detect, according to functionalities, different types of traffic generated by a single application and should increase completeness by reducing the amount of undetected traffic. We verify our method with real-world traffic. Our performance comparison against existing DPI-based classification frameworks shows that the fine-grained classification scheme achieves consistently higher accuracyand completeness. Copyright (c) 2013 John Wiley & Sons, Ltd. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | WILEY | - |
dc.subject | INTERNET | - |
dc.subject | ALGORITHM | - |
dc.title | Fine-grained traffic classification based on functional separation | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Myung-sup | - |
dc.identifier.doi | 10.1002/nem.1837 | - |
dc.identifier.scopusid | 2-s2.0-84884127330 | - |
dc.identifier.wosid | 000324330900003 | - |
dc.identifier.bibliographicCitation | INTERNATIONAL JOURNAL OF NETWORK MANAGEMENT, v.23, no.5, pp.350 - 381 | - |
dc.relation.isPartOf | INTERNATIONAL JOURNAL OF NETWORK MANAGEMENT | - |
dc.citation.title | INTERNATIONAL JOURNAL OF NETWORK MANAGEMENT | - |
dc.citation.volume | 23 | - |
dc.citation.number | 5 | - |
dc.citation.startPage | 350 | - |
dc.citation.endPage | 381 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.subject.keywordPlus | INTERNET | - |
dc.subject.keywordPlus | ALGORITHM | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.