A Novel Features Set for Internet Traffic Classification using Burstiness
dc.contributor.author | Oudah, H | |
dc.contributor.author | Ghita, B | |
dc.contributor.author | Bakhshi, T | |
dc.contributor.editor | Mori P | |
dc.contributor.editor | Furnell S | |
dc.contributor.editor | Camp O | |
dc.date.accessioned | 2022-11-07T12:10:01Z | |
dc.date.available | 2022-11-07T12:10:01Z | |
dc.date.issued | 2019 | |
dc.identifier.isbn | 9789897583599 | |
dc.identifier.uri | http://hdl.handle.net/10026.1/19886 | |
dc.description.abstract |
Traffic classification is an essential tool for network management and security. Traditional techniques such as port-based and payload analysis are ineffective as major Internet applications use dynamic port numbers and encryption. Recent studies have used statistical properties of flows to classify traffic with high accuracy, minimising the overhead limitations associated with other schemes such as deep packet inspection (DPI). Classification accuracy of statistical flow-based approaches, however, depends on the discrimination ability of the traffic features used. To this effect, the present paper customised the popular tcptrace utility to generate classification features based on traffic burstiness and periods of inactivity (idle time) for everyday Internet usage. An attempt was made to train a C5.0 decision tree classifier using the proposed features for eleven different Internet applications, generated by ten users. Overall, the newly proposed features reported a significant level of accuracy (∼98%) in classifying the respective applications. | |
dc.format.extent | 397-404 | |
dc.language.iso | en | |
dc.publisher | SCITEPRESS - Science and Technology Publications | |
dc.subject | Traffic Classification | |
dc.subject | Tcptrace | |
dc.subject | Application Detection | |
dc.subject | C5.0 Algorithm | |
dc.title | A Novel Features Set for Internet Traffic Classification using Burstiness | |
dc.type | conference | |
dc.type | Conference Proceeding | |
plymouth.author-url | https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000570402400042&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008 | |
plymouth.date-start | 2019-02-23 | |
plymouth.date-finish | 2019-02-25 | |
plymouth.publisher-url | http://www.informatik.uni-trier.de/~ley/db/conf/icissp/icissp2019.html | |
plymouth.conference-name | 5th International Conference on Information Systems Security and Privacy | |
plymouth.publication-status | Published | |
plymouth.journal | Proceedings of the 5th International Conference on Information Systems Security and Privacy | |
dc.identifier.doi | 10.5220/0007384203970404 | |
plymouth.organisational-group | /Plymouth | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics | |
plymouth.organisational-group | /Plymouth/Users by role | |
plymouth.organisational-group | /Plymouth/Users by role/Academics | |
dc.rights.embargoperiod | Not known | |
rioxxterms.versionofrecord | 10.5220/0007384203970404 | |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | |
rioxxterms.type | Conference Paper/Proceeding/Abstract |