Modeling Expert Judgments of Insider Threat Using Ontology Structure: Effects of Individual Indicator Threat Value and Class Membership

dc.contributor.author Greitzer, Frank
dc.contributor.author Purl, Justin
dc.contributor.author Becker, D.E. (Sunny)
dc.contributor.author Sticha, Paul
dc.contributor.author Leong, Yung Mei
dc.date.accessioned 2019-01-03T00:13:05Z
dc.date.available 2019-01-03T00:13:05Z
dc.date.issued 2019-01-08
dc.description.abstract We describe research on a comprehensive ontology of sociotechnical and organizational factors for insider threat (SOFIT) and results of an expert knowledge elicitation study. The study examined how alternative insider threat assessment models may reflect associations among constructs beyond the relationships defined in the hierarchical class structure. Results clearly indicate that individual indicators contribute differentially to expert judgments of insider threat risk. Further, models based on ontology class structure more accurately predict expert judgments. There is some (although weak) empirical evidence that other associations among constructs—such as the roles that indicators play in an insider threat exploit—may also contribute to expert judgments of insider threat risk. These findings contribute to ongoing research aimed at development of more effective insider threat decision support tools.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2019.387
dc.identifier.isbn 978-0-9981331-2-6
dc.identifier.uri http://hdl.handle.net/10125/59756
dc.language.iso eng
dc.relation.ispartof Proceedings of the 52nd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Inside the Insider Threats
dc.subject Digital Government
dc.subject insider threat, ontology, threat assessment
dc.title Modeling Expert Judgments of Insider Threat Using Ontology Structure: Effects of Individual Indicator Threat Value and Class Membership
dc.type Conference Paper
dc.type.dcmi Text
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