SecureAI: Toward Experiential Security and Privacy Training for AI Practitioners
Cover - CISSE Volume 13, Issue 1
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Keywords

AI security
cybersecurity training
privacy-preserving AI
experiential learning
professional development
adversarial machine learning

Abstract

The rapid adoption of artificial intelligence across industries has outpaced security and privacy training for AI practitioners. This paper presents methods, modules, and findings from an experiential training program designed to address security and privacy challenges in AI systems development and deployment. We conducted two program iterations: a comprehensive 12-workshop series (May-October 2024) and a condensed 6-workshop format (January-February 2025). The program combined expert-led panel sessions with hands-on laboratory activities, engaging 78 participants from diverse professional backgrounds. Evaluation through pre- and post-evaluation surveys and qualitative observations revealed improvements in cybersecurity knowledge and AI security awareness. Participants demonstrated enhanced ability to identify vulnerabilities, implement security measures, and develop organizational policies for AI-related risk mitigation. The condensed format showed comparable learning outcomes with improved completion rates. This effort highlights the increased need to establish cybersecurity and privacy training for AI professionals to develop secure and trustworthy AI systems.

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