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dc.contributor.authorKhan, Muhammad Imran
dc.contributor.authorFoley, Simon N.
dc.contributor.authorO'Sullivan, Barry
dc.date.accessioned2021-03-05T10:34:55Z
dc.date.available2021-03-05T10:34:55Z
dc.date.created2020-10-28T13:26:39Z
dc.date.issued2020
dc.identifier.citationProcedia Computer Science. 2020, 175 331-339.en_US
dc.identifier.issn1877-0509
dc.identifier.urihttps://hdl.handle.net/11250/2731808
dc.description.abstractIn this paper a notion of privacy-anomaly detection is presented where normative privacy is modelled using k-anonymity. Based on the model, normative privacy-profiles are constructed, and deviation from normative privacy-profile at runtime is labelled as a privacy-anomaly. Furthermore, the paper investigates whether there is a correlation between security-anomalies and privacy-anomalies, that is, whether the privacy-anomalies labelled by privacy-anomaly detection system are detected by conventional security-anomaly detection system used for detecting malicious accesses to databases by insiders.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleTowards Privacy-anomaly Detection: Discovering Correlation between Privacy and Security-anomaliesen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber331-339en_US
dc.source.volume175en_US
dc.source.journalProcedia Computer Scienceen_US
dc.identifier.doi10.1016/j.procs.2020.07.048
dc.identifier.cristin1842950
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
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