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dc.contributor.convenorIEEE Intelligent Transportation Systems Society
dc.contributor.authorEstivill-Castro, V
dc.contributor.authorHajyasien, A
dc.contributor.editorGheorghe Muresan, Tayfur Altiok, Banjamin Melamed and Daniel Seng
dc.date.accessioned2017-05-03T14:15:54Z
dc.date.available2017-05-03T14:15:54Z
dc.date.issued2007
dc.date.modified2008-05-26T02:08:20Z
dc.identifier.isbn9781424413300
dc.identifier.doi10.1109/ISI.2007.379492
dc.identifier.urihttp://hdl.handle.net/10072/17665
dc.description.abstractPrivacy concerns may discourage users who would otherwise join beneficial data mining tasks for intelligence and/or security. We propose an efficient protocol that allows parties to share data in a private way with no restrictions and without loss of accuracy. Our method has the immediate application that horizontally partitioned databases can be brought together and made public without disclosing the source/owner of each record. At another level, we have an additional benefit that we can apply our protocol to privately discover association rules. Our protocol is more efficient than previous methods. The effects of our protocol are less than others: 1) each party can identify only their data, 2) no party is able to learn the links between other parties and their data, 3) no party learns any transactions of the other parties' databases.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent2021453 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoen_AU
dc.publisherIEEE
dc.publisher.placePiscataway, NJ
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofconferencenameIntelligence and Security Informatics 2007
dc.relation.ispartofconferencetitleISI 2007: 2007 IEEE Intelligence and Security Informatics
dc.relation.ispartofdatefrom2007-05-23
dc.relation.ispartofdateto2007-05-24
dc.relation.ispartoflocationNew Brunswick, NJ, USA
dc.relation.ispartofpagefrom325
dc.relation.ispartofpageto331
dc.rights.retentionY
dc.subject.fieldofresearchcode280505
dc.titleFast Private Association Rule Mining by A Protocol for Securely Sharing Distributed Data
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.rights.copyright© 2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
gro.date.issued2007
gro.hasfulltextFull Text
gro.griffith.authorEstivill-Castro, Vladimir


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    Contains papers delivered by Griffith authors at national and international conferences.

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