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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Evaluating Personal Data Control In Mobile Applications Using Heuristics

Alain Giboin (UCA, INRIA, CNRS, I3S), Karima Boudaoud (UCA, CNRS, I3S), Patrice Pena (Userthink), Yoann Bertrand (UCA, CNRS, I3S), Fabien Gandon (UCA, INRIA, CNRS, I3S)

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PBP: Post-training Backdoor Purification for Malware Classifiers

Dung Thuy Nguyen (Vanderbilt University), Ngoc N. Tran (Vanderbilt University), Taylor T. Johnson (Vanderbilt University), Kevin Leach (Vanderbilt University)

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Impact Tracing: Identifying the Culprit of Misinformation in Encrypted...

Zhongming Wang (Chongqing University), Tao Xiang (Chongqing University), Xiaoguo Li (Chongqing University), Biwen Chen (Chongqing University), Guomin Yang (Singapore Management University), Chuan Ma (Chongqing University), Robert H. Deng (Singapore Management University)

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BrowserFM: A Feature Model-based Approach to Browser Fingerprint Analysis

Maxime Huyghe (Univ. Lille, Inria, CNRS, UMR 9189 CRIStAL), Clément Quinton (Univ. Lille, Inria, CNRS, UMR 9189 CRIStAL), Walter Rudametkin (Univ. Rennes, Inria, CNRS, UMR 6074 IRISA)

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