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Where Did They Go Right? Understanding the Deception in Phishing Communications

Author

Listed:
  • Ryan Wright

    (The University of San Francisco)

  • Suranjan Chakraborty

    (Towson University)

  • Asli Basoglu

    (Washington State University)

  • Kent Marett

    (Mississippi State University)

Abstract

Deceptive communication through phishing is becoming more pervasive with the spread of ubiquitous computing. Yet, phishing has not been widely understood or studied even when such practices cost organizations millions of dollars each year. This manuscript tests Grazioli’s Theory of Deception as an explanation for the process utilized to detect phishing attempts. In order to test the detection model, the paper phished 446 subjects for confidential information. The results consist of a structural model tested to determine experiential and dispositional characteristics of deception detectors. Subsequently, the authors interviewed the detectors and elicited a rich account of how the subjects processed and formed a correct behavioral decision upon receiving the phishing email. These interviews provided additional insight toward the specific processes of successful deception detectors used upon the receipt of a phishing email. The results from both the statistical testing and the interview data analysis confirmed and added to the Model of Deception Detection.

Suggested Citation

  • Ryan Wright & Suranjan Chakraborty & Asli Basoglu & Kent Marett, 2010. "Where Did They Go Right? Understanding the Deception in Phishing Communications," Group Decision and Negotiation, Springer, vol. 19(4), pages 391-416, July.
  • Handle: RePEc:spr:grdene:v:19:y:2010:i:4:d:10.1007_s10726-009-9167-9
    DOI: 10.1007/s10726-009-9167-9
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    References listed on IDEAS

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    1. Deborah R. Compeau & Christopher A. Higgins, 1995. "Application of Social Cognitive Theory to Training for Computer Skills," Information Systems Research, INFORMS, vol. 6(2), pages 118-143, June.
    2. Johnson, Paul E. & Grazioli, Stefano & Jamal, Karim, 1993. "Fraud detection: Intentionality and deception in cognition," Accounting, Organizations and Society, Elsevier, vol. 18(5), pages 467-488, July.
    3. Stefano Grazioli, 2004. "Where Did They Go Wrong? An Analysis of the Failure of Knowledgeable Internet Consumers to Detect Deception Over the Internet," Group Decision and Negotiation, Springer, vol. 13(2), pages 149-172, March.
    4. Segars, A. H., 1997. "Assessing the unidimensionality of measurement: a paradigm and illustration within the context of information systems research," Omega, Elsevier, vol. 25(1), pages 107-121, February.
    5. Naresh K. Malhotra & Sung S. Kim & James Agarwal, 2004. "Internet Users' Information Privacy Concerns (IUIPC): The Construct, the Scale, and a Causal Model," Information Systems Research, INFORMS, vol. 15(4), pages 336-355, December.
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    Cited by:

    1. Sirkka L. Jarvenpaa & Ann Majchrzak, 2010. "Research Commentary ---Vigilant Interaction in Knowledge Collaboration: Challenges of Online User Participation Under Ambivalence," Information Systems Research, INFORMS, vol. 21(4), pages 773-784, December.
    2. Kim Kaivanto, 2014. "The Effect of Decentralized Behavioral Decision Making on System‐Level Risk," Risk Analysis, John Wiley & Sons, vol. 34(12), pages 2121-2142, December.
    3. Xin Wen & Liang Xu & Jie Wang & Yuan Gao & Jiaming Shi & Ke Zhao & Fuyang Tao & Xiuying Qian, 2022. "Mental States: A Key Point in Scam Compliance and Warning Compliance in Real Life," IJERPH, MDPI, vol. 19(14), pages 1-16, July.
    4. Liuchang Xu & Jie Wang & Dayu Xu & Liang Xu, 2022. "Integrating Individual Factors to Construct Recognition Models of Consumer Fraud Victimization," IJERPH, MDPI, vol. 19(1), pages 1-12, January.
    5. Matthew Canham & Clay Posey & Delainey Strickland & Michael Constantino, 2021. "Phishing for Long Tails: Examining Organizational Repeat Clickers and Protective Stewards," SAGE Open, , vol. 11(1), pages 21582440219, January.

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