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dc.contributor.authorSzekeres, Adam
dc.contributor.authorSnekkenes, Einar Arthur
dc.identifier.citationIEEE Access. 2020, 8 45096-45107.en_US
dc.description.abstractThis study aimed at analyzing the extent to which publicly observable pieces of information representing stakeholders’ past and current choices can be utilized for the construction of motivational profiles. Motivation is operationalized by the theory of Basic Human Values, which organizes 10 values capturing distinct aspects of human motivation into a hierarchical order. The construction of motivational profiles for individual stakeholders is motivated by the need to enhance the existing decision-maker model in the Conflicting Incentives Risk Analysis (CIRA) method. This study utilized an online questionnaire to collect responses from participants (n = 331) about a wide range of habits and personal items that are easily observable in various contexts by an analyst. The validity of the set of observables as surrogate predictors of the motivational profiles is evaluated by various methods (i.e., comparison to previous results, cross-validation of models, comparison to test-retest reliability of the psychometric instrument) and techniques (calculation of prediction interval for individual profile scores). The assessment of the uncertainties associated with predicting motivational profiles is explored in detail. Additionally, an example illustrates how the profiles can be utilized for the assessment of action desirability (i.e., prediction of behavior) based on the utility calculations established in CIRA. The results contribute to an improved understanding about the accuracy with which human stakeholder motivation can be inferred from public observables and utilized within the context of information security risk analysis.en_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.titleConstruction of Human Motivational Profiles by Observation for Risk Analysisen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.source.journalIEEE Accessen_US
dc.description.localcodeThis work is licensed under a Creative Commons Attribution 4.0 License. For more information, see
cristin.unitnameInstitutt for informasjonssikkerhet og kommunikasjonsteknologi

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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal