Wednesday, October 28, 2026
9:00 AM – 5:00 PM CDT
GAISS 2026 — IEEE Conference on Generative AI for Secure Systems
About this event
A three-day peer-reviewed IEEE conference at UT Austin on the security of generative AI, spanning adversarial robustness, agentic autonomy, red-team automation, and AI governance, with papers indexed in IEEE Xplore.
Where generative AI meets security research
GAISS 2026 is an IEEE conference devoted to trustworthy generative AI, held at the University of Texas at Austin. Accepted papers go through double-blind review and are indexed in IEEE Xplore, so this is a genuine research venue rather than a vendor showcase — though the organizers describe an audience that deliberately mixes academics working on adversarial robustness, security teams defending production pipelines, and policymakers.
The announced tracks cover threat intelligence and adversary simulation, robust generative models in adversarial settings, DevSecOps and code security, critical infrastructure and IoT, quantum machine learning and security, synthetic and federated data with privacy preservation, secure networking, human–AI collaboration and governance, automated red- and blue-teaming, and agentic autonomous systems.
Registration is tiered by academic or industry affiliation and by IEEE membership, running roughly from early-bird academic rates up to onsite industry rates; check the ticketing page for current pricing. The paper submission deadline is August 15, 2026.
Note on times: the organizers publish the October 28–30 date range but have not released a daily schedule. The 9:00 a.m. start shown here is provisional — confirm session times on the official site before booking travel.
Organized by
The Institute of Electrical and Electronics Engineers, the professional body whose conferences publish peer-reviewed research through IEEE Xplore, including the GAISS conference on generative AI for secure systems.