Business adoption of generative AI (GenAI) is surging, with teams like yours integrating GenAI with corporate documents, databases, and other internal repositories to address domain-specific problems and use cases. But with this accelerated deployment comes a heightened risk profile from several types of adversarial machine learning (AML) attacks, including theft, compromise, and escape of both ML data and models themselves.

Join us for an enlightening discussion, where we'll explore prescriptive ways you can secure your GenAI systems against emerging, and rapidly evolving, AML dangers.

What you will learn:

•  Specific AML tactics threat actors use to corrupt GenAI availability and operational integrity

•  The risks associated with ML model tampering—and how to uphold your business's reputation

•  Concrete strategies to thwart adversaries attempting to make unauthorized changes to your data and model sources

•  The critical role of secure code signing processes in establishing authenticity and integrity throughout your AI system supply chain

Whether you're a business leader or a cybersecurity practitioner, you can't afford to overlook the fortification of your GenAI systems. This session will equip you with the knowledge and strategies you need to safeguard the future of your AI-augmented enterprise.

Attendees are eligible to receive 1 CPE credit.

Generously supported by:

supported by logo
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Faisal Razzak
Group Manager, Post Quantum & Secure Software Supply Chain Initiatives, Research & Development, Venafi
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Tom Bechtold
Digital Events Director, SecureWorld
Tom has been part of the SecureWorld team for more than 14 years. He has launched several of the regional conferences we hold today. Tom is currently responsible for SecureWorld Digital, which provides educational content to the SecureWorld audience. He produces, executes, and moderates the majority of the Remote Sessions webcasts while also working closely with the SecureWorld event directors to build relevant agendas at the regional conferences.