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Predicting Ethical Orientation Based on Personality for Tailored Cyberethics Training

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Persuasive Technology (PERSUASIVE 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14636))

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Abstract

A lack of training in the ethical aspects of decision making among cybersecurity professionals can lead to an increased risk of cyber breaches. We have developed a serious game to provide training to increase players’ awareness of five ethical principles relevant to decision making in common cybersecurity situations. By understanding what ethical principles currently drive that individual, we plan to tailor the game’s scenarios and dialogues to be more persuasive in presenting alternative viewpoints in order to improve the ethical reasoning capability of players and their ability to make ethically informed cybersecurity decisions. The literature suggests that personality is a predictor of ethical behaviour. Thus, as the basis for tailoring, we seek to use personality to predict the player’s priority for each of our five focus ethical principles. This paper reports our attempts to build and validate models based on data we collected from three different studies using our cyberethics game.

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Authors and Affiliations

  1. School of Computing, Macquarie University, Sydney, NSW, 2109, Australia

    Muhammad Hassan Ali Bajwa & Deborah Richards

  2. School of Philosophy, Macquarie University, Sydney, NSW, 2109, Australia

    Paul Formosa

Authors
  1. Muhammad Hassan Ali Bajwa
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  2. Deborah Richards
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  3. Paul Formosa
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Corresponding author

Correspondence to Muhammad Hassan Ali Bajwa .

Editor information

Editors and Affiliations

  1. The University of Queensland, St Lucia, QLD, Australia

    Nilufar Baghaei

  2. Hamad Bin Khalifa University, Doha, Qatar

    Raian Ali

  3. University of Wollongong, Wollongong, NSW, Australia

    Khin Win

  4. York University, Toronto, ON, Canada

    Kiemute Oyibo

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Bajwa, M.H.A., Richards, D., Formosa, P. (2024). Predicting Ethical Orientation Based on Personality for Tailored Cyberethics Training. In: Baghaei, N., Ali, R., Win, K., Oyibo, K. (eds) Persuasive Technology. PERSUASIVE 2024. Lecture Notes in Computer Science, vol 14636. Springer, Cham. https://doi.org/10.1007/978-3-031-58226-4_6

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  • DOI: https://doi.org/10.1007/978-3-031-58226-4_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-58225-7

  • Online ISBN: 978-3-031-58226-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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