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Predicting personal susceptibility to phishing
Norwegian Computing Center, Oslo, Norway.ORCID-id: 0000-0003-3214-2495
Umeå universitet, Samhällsvetenskapliga fakulteten, Institutionen för informatik. (Q-life)ORCID-id: 0000-0001-9419-0682
2020 (engelsk)Inngår i: Information technology and systems: proceedings of ICITS 2020 / [ed] Álvaro Rocha, Carlos Ferrás, Carlos Enrique Montenegro Marin, Víctor Hugo Medina García, Cham: Springer, 2020, 1, s. 564-575Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Phishing is a confidence trick with damaging impacts on both individuals and society as a whole. In this paper, we examine the possible role of thinking styles, as assessed by the Cognitive Reflection Test (CRT), and other factors to predict personal susceptibility to phishes. We report the results of two large-scale national studies conducted on cross-sectional populations in Norway. Using a binary logistic regression method, we analyzed the relationship between CRT scores, willingness to share data and demographical variables, to susceptibility to comply with phishes. Our main finding was that both an intuitive thinking style, as operationalized by the CRT scores, and willingness to share personal, significantly predict the probability of falling for phishing. As these results are based on two large-scale studies of national populations, they can be expected to have greater validity than earlier studies. The finding that CRT scores and other personal characteristics can predict the likelihood of falling for phishing suggests methods of pre-emptive testing of individuals as part of private and organizational strategies for encouraging improved resistance to phishing and other forms of personal data theft.

sted, utgiver, år, opplag, sider
Cham: Springer, 2020, 1. s. 564-575
Serie
Advances in Intelligent Systems and Computing, ISSN 2194-5357, E-ISSN 2194-5365 ; 1137
Emneord [en]
Susceptibility to phishing, Cognitive Reflection Test, national samples, data disclosure, privacy
HSV kategori
Forskningsprogram
människa-datorinteraktion
Identifikatorer
URN: urn:nbn:se:umu:diva-164291DOI: 10.1007/978-3-030-40690-5_54ISBN: 9783030406899 (tryckt)ISBN: 9783030406905 (digital)OAI: oai:DiVA.org:umu-164291DiVA, id: diva2:1362603
Konferanse
ICITS'20: The 2020 International Conference on Information Technology & Systems, Bogotá, Colombia, February 5-7, 2020
Tilgjengelig fra: 2019-10-21 Laget: 2019-10-21 Sist oppdatert: 2020-05-28bibliografisk kontrollert

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