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Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/62244
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dc.contributor.authorIslam, Md Zahidulen
dc.contributor.authorBrankovic, Ljiljanaen
local.source.editorEditor(s): J. Hogan, P. Montague, M. Purvis and C. Steketeeen
dc.date.accessioned2024-08-19T01:14:20Z-
dc.date.available2024-08-19T01:14:20Z-
dc.date.issued2004-
dc.identifier.citationACSW Frontiers '04: Proceedings of the second workshop on Australasian information security, Data Mining and Web Intelligence, and Software Internationalisation - Volume 32, v.32, p. 163-168en
dc.identifier.urihttps://hdl.handle.net/1959.11/62244-
dc.description.abstract<p>Nowadays organizations all over the world are dependent on mining gigantic datasets. These datasets typically contain delicate individual information, which inevitably gets exposed to different parties. Consequently privacy issues are constantly under the limelight and the public dissatisfaction may well threaten the exercise of data mining and all its benefits. It is thus of great importance to develop adequate security techniques for protecting confidentiality of individual values used for data mining.</p>en
dc.languageenen
dc.publisherAustralian Computer Society, Incen
dc.relation.ispartofACSW Frontiers '04: Proceedings of the second workshop on Australasian information security, Data Mining and Web Intelligence, and Software Internationalisation - Volume 32en
dc.titleA Framework for Privacy Preserving Classification in Data Miningen
dc.typeConference Publicationen
dc.relation.conferenceACSW 2004: Australian Computer Science Week (ACSW ) Conferenceen
local.contributor.firstnameMd Zahidulen
local.contributor.firstnameLjiljanaen
local.profile.schoolSchool of Science and Technologyen
local.profile.emaillbrankov@une.edu.auen
local.output.categoryE1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.date.conference18th - 22nd January, 2004en
local.conference.placeDunedin, New Zealanden
local.format.startpage163en
local.format.endpage168en
local.peerreviewedYesen
local.identifier.volume32en
local.contributor.lastnameIslamen
local.contributor.lastnameBrankovicen
dc.identifier.staffune-id:lbrankoven
local.profile.orcid0000-0002-5056-4627en
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/62244en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleA Framework for Privacy Preserving Classification in Data Miningen
local.output.categorydescriptionE1 Refereed Scholarly Conference Publicationen
local.relation.urlhttps://dl.acm.org/doi/10.5555/976440.976465en
local.conference.detailsACSW 2004: Australian Computer Science Week (ACSW ) Conference, Dunedin, New Zealand, 18th - 22nd January, 2004en
local.search.authorIslam, Md Zahidulen
local.search.authorBrankovic, Ljiljanaen
local.uneassociationNoen
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.published2004en
local.fileurl.closedpublishedhttps://rune.une.edu.au/web/retrieve/16eefdff-3dcc-4497-ae97-c4a97d79aa10en
local.subject.for2020460402 Data and information privacyen
local.subject.seo2020229999 Other information and communication services not elsewhere classifieden
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
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School of Science and Technology
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