About the Conference
Generative AI Meets Security Engineering
The IEEE Conference on Generative AI for Secure Systems (GAISS) addresses security for generative models and their deployment in production systems: threat modeling, defensive design, and assurance for models and inference pipelines. Papers accepted for presentation are published in IEEE proceedings and indexed in IEEE Xplore.
The program combines peer-reviewed research with applied sessions from industry and government. Participants include academic researchers, product and platform teams, and security engineers, with emphasis on comparable methods, reproducible results, and clear criteria for evaluation.
WHAT PEOPLE SAY
Voices from the Community
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GAISS brought together the exact intersection of AI and security that our industry needs. The caliber of speakers and depth of technical sessions was outstanding.
Dr. Sarah Kim
Research Lead, MIT CSAIL
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The networking alone was worth the trip. I left with three new research collaborations and a completely different perspective on LLM security.
James Okafor
CTO, ShieldAI
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As a PhD student, presenting at GAISS was a career-defining moment. The feedback from industry leaders was invaluable.
Priya Sharma
PhD Candidate, Stanford University
JOIN US
Secure Generative AI Starts With
Shared Standards.
GAISS is the IEEE venue where published research, product practice, and policy pressure meet on generative AI security. Join researchers, engineers, and decision-makers at The University of Texas at Austin for October 28 to 30, 2026. Three days to align on what to build and how to measure it.
Early bird pricing until September 28