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Rodgers, Waymond and Murray, James M. and Strashnoy, Leonard and Lande, Dmytro
Ethical Auditors' Framework for Generative Ai Cybersecurity

Available at SSRN: https://ssrn.com/abstract=4800215,
DOI: http://dx.doi.org/10.2139/ssrn.4800215 (19 Apr 2024). 32 pages.

Ethical dilemmas and compromises are introduced when identifying, mitigating, and addressing solutions to cybersecurity vulnerabilities. The accelerated use of generative AI platforms presents opportunities for cybersecurity professional auditors to analyze possible approaches in identifying the drivers and possible solutions in addressing vulnerabilities such as fraud. In this paper we seek to introduce a structured approach to addressing ethics for auditors' cybersecurity decision-making, rooted in scenario-planning to support agility in cybersecurity. Building on Causal Network research using ChatGPT, we introduce an ethical framework for generative AI cybersecurity using algorithmic ethical pathways.
Keywords: Cybersecurity, Ethics, Causal Networks, ChatGPT, Generative AI