The Databricks Security team led a broad working group that significantly evolved the Databricks AI Security Framework (DASF) to its 2.0 version since its first release by closely collaborating with the top cyber security researchers at industry organizations such as OWASP, Gartner, NIST, HITRUST, FAIR Institute and several Fortune 100 companies to address the evolving risks and associated controls of AI systems in enterprises. Join us to to learn how The CLEVER GenAI pipeline, an AI-driven innovation in healthcare, processes over 1.5 million clinical notes daily to classify social determinants impacting veteran care while adhering to robust security measures like NIST 800-53 controls and by leveraging Databricks AI Security Framework. We will discuss robust AI security guidelines to help data and AI teams understand how to deploy their AI applications securely. This session will give a security framework for security teams, AI practitioners, data engineers and governance teams.

This session is repeated. AI is transforming industries, enhancing customer experiences and automating decisions. As organizations integrate AI into core operations, robust security is essential. The Databricks Security team collaborated with top cybersecurity researchers from OWASP, Gartner, NIST, HITRUST and Fortune 100 companies to evolve the Databricks AI Security Framework (DASF) to version 2.0. In this session, we’ll cover an AI security architecture using Unity Catalog, MLflow, egress controls, and AI gateway. Learn how security teams, AI practitioners and data engineers can secure AI applications on Databricks. Walk away with:• A reference architecture for securing AI applications• A worksheet with AI risks and controls mapped to industry standards like MITRE, OWASP, NIST and HITRUST• A DASF AI assistant tool to test your AI security