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Explore the critical intersection of artificial intelligence security and Zero Trust architecture in this comprehensive conference talk that examines how to protect multi-agent AI systems handling sensitive data. Discover the leading technical trends accelerating Agentic AI adoption across industries and understand why traditional security approaches fall short when applied to these sophisticated systems. Learn to dissect the fundamental architectural layers that comprise Agentic AI systems, from data ingestion and processing to decision-making and output generation. Master a practical seven-layer threat modeling framework specifically designed to identify, assess, and mitigate security vulnerabilities unique to multi-agent environments. Gain insights into real-world attack vectors that target AI agents, including data poisoning, model manipulation, and inter-agent communication breaches. Examine case studies demonstrating how Zero Trust principles can be effectively implemented across distributed AI architectures to ensure data privacy and system integrity. Access practical guidance on deploying an open-source security framework that provides immediate protection for your AI implementations while maintaining operational efficiency and scalability.
