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Skype Traffic Classification Using Cost Sensitive Algorithms

Azab, Ahmad; Layton, Robert; Alazab, Mamoun; Watters, Paul

Description

Voice over IP (VoIP) technologies such as Skype are becoming increasingly popular and widely used in different organisations, and therefore identifying the usage of this service at the network level becomes very important. Reasons for this include applying Quality of Service (QoS), network planning, prohibiting its use in some networks and lawful interception of communications. Researchers have addressed VoIP traffic classification from different viewpoints, such as classifier accuracy,...[Show more]

dc.contributor.authorAzab, Ahmad
dc.contributor.authorLayton, Robert
dc.contributor.authorAlazab, Mamoun
dc.contributor.authorWatters, Paul
dc.coverage.spatialSydney Australia
dc.date.accessioned2015-12-10T23:09:51Z
dc.date.createdNovember 2013
dc.identifier.isbn9781479930753
dc.identifier.urihttp://hdl.handle.net/1885/63471
dc.description.abstractVoice over IP (VoIP) technologies such as Skype are becoming increasingly popular and widely used in different organisations, and therefore identifying the usage of this service at the network level becomes very important. Reasons for this include applying Quality of Service (QoS), network planning, prohibiting its use in some networks and lawful interception of communications. Researchers have addressed VoIP traffic classification from different viewpoints, such as classifier accuracy, building time, classification time and online classification. This previous research tested their models using the same version of a VoIP product they used for training the model, giving generalizability only to that version of the product. This means that as new VoIP versions are released, these classifiers become obsolete. In this paper, we address if this approach is applicable to detecting new, untrained, versions of Skype. We suggest that using cost-sensitive classifiers can help to improve the accuracy of detecting untrained versions, by testing compared to other algorithms. Our experiment demonstrates promising preliminary results to detect Skype version 4, by building a cost sensitive classifier on Skype version 3, achieving an F-measure score of 0.57. This is a drastic improvement from not using cost sensitivity, which scores an F-measure of 0. This approach may be enhanced to improve the detection results and extended to improve detection for other applications that change protocols from version to version.
dc.publisherIEEE
dc.relation.ispartofseries4th Cybercrime and Trustworthy Computing Workshop (CTC-2013)
dc.sourceMalicious Spam Emails Developments and Authorship Attribution
dc.titleSkype Traffic Classification Using Cost Sensitive Algorithms
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2013
local.identifier.absfor160201 - Causes and Prevention of Crime
local.identifier.absfor160206 - Private Policing and Security Services
local.identifier.absfor160299 - Criminology not elsewhere classified
local.identifier.ariespublicationU3488905xPUB811
local.type.statusPublished Version
local.contributor.affiliationAzab, Ahmad, University of Ballarat
local.contributor.affiliationLayton, Robert, University of Ballarat
local.contributor.affiliationAlazab, Mamoun, College of Asia and the Pacific, ANU
local.contributor.affiliationWatters, Paul, University of Ballarat
local.description.embargo2037-12-31
local.bibliographicCitation.startpage14
local.bibliographicCitation.lastpage21
local.identifier.doi10.1109/CTC.2013.11
local.identifier.absseo810107 - National Security
local.identifier.absseo940402 - Crime Prevention
local.identifier.absseo970108 - Expanding Knowledge in the Information and Computing Sciences
dc.date.updated2015-12-10T09:14:38Z
local.identifier.scopusID2-s2.0-84898038592
CollectionsANU Research Publications

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