Rishika Thorat (Purdue University), Tatiana Ringenberg (Purdue University)

AI-assisted cybersecurity policy development has the potential to reduce organizational burdens while improving compliance. This study examines how cybersecurity students and professionals develop ISO29147-aligned vulnerability disclosure policies (VDPs) with and without AI. Through this project, we will evaluate compliance, ethical accountability, and transparency of the policies through the lens of Kaspersky’s ethical principles.

Both students and professionals will produce policies manually and with AI, reflecting on utility and reliability. We will analyze resulting policies, prompts, and reflections through regulatory mapping, rubric-based evaluations, and thematic analysis. This project aims to inform educational strategies and industry best practices for integrating AI in cybersecurity policy development, focusing on expertise, collaboration, and ethical considerations.

We invite feedback from the Usable Security and Privacy community on participant recruitment, evaluation criteria, ethical frameworks, and ways to maximize the study’s impact on academia and industry.

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S. P. Veed, S. M. Daftary, B. Singh, M. Rudra, S. Berhe (University of the Pacific), M. Maynard (Data Independence LLC) F. Khomh (Polytechnique Montreal)

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Shixin Song (Massachusetts Institute of Technology), Joseph Zhang (Massachusetts Institute of Technology), Mengjia Yan (Massachusetts Institute of Technology)

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Jingwen Yan (Clemson University), Mohammed Aldeen (Clemson University), Jalil Harris (Clemson University), Kellen Grossenbacher (Clemson University), Aurore Munyaneza (Texas Tech University), Song Liao (Texas Tech University), Long Cheng (Clemson University)

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