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dc.contributor.authorClarke, Nathan
dc.contributor.authorLi, F
dc.contributor.authorAlruban, A
dc.contributor.authorFurnell, S
dc.date.accessioned2022-04-25T10:53:27Z
dc.date.available2022-04-25T10:53:27Z
dc.date.issued2017
dc.identifier.issn2572-6862
dc.identifier.urihttp://hdl.handle.net/10026.1/19064
dc.description.abstract

Insider misuse is a key threat to organizations. Recent research has focused upon the information itself – either through its protection or approaches to detect the leakage. This paper seeks a different approach through the application of transparent biometrics to provide a robust approach to the identification of the individuals who are misusing systems and information. Transparent biometrics are a suite of modalities, typically behavioral-based that can capture biometric signals covertly or non-intrusively – so the user is unaware of their capture. Transparent biometrics are utilized in two phases a) to imprint digital objects with biometric-signatures of the user who last interacted with the object and b) uniquely applied to network traffic in order to identify users traffic (independent of the Internet Protocol address) so that users rather than machine (IP) traffic can be more usefully analyzed by analysts. Results from two experimental studies are presented and illustrate how reliably transparent biometrics are in providing this link-ability of information to identity.

dc.format.extent4031-4040
dc.language.isoen
dc.publisherHawaii International Conference on System Sciences
dc.titleInsider Misuse Identification using Transparent Biometrics
dc.typeconference
plymouth.author-urlhttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000625875705056&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008
plymouth.conference-nameHawaii International Conference on System Sciences
plymouth.publication-statusPublished
plymouth.journalProceedings of the 50th Hawaii International Conference on System Sciences (2017)
dc.identifier.doi10.24251/hicss.2017.487
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
dcterms.dateAccepted2017-01-01
dc.rights.embargodate2022-4-26
dc.rights.embargoperiodNot known
rioxxterms.versionofrecord10.24251/hicss.2017.487
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.typeConference Paper/Proceeding/Abstract


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