Databricks Best Practices to Mitigate AI Security Risks
Overview
Experience | In Person |
---|---|
Type | Breakout |
Track | Data and AI Governance |
Industry | Health and Life Sciences, Public Sector, Financial Services |
Technologies | MLFlow, Mosaic AI, Unity Catalog |
Skill Level | Intermediate |
Duration | 40 min |
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
Session Speakers
Arun Pamulapati
/Principal Staff Security Field Engineer
Databricks
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Samrat Ray
/Senior Staff Product Manager
Databricks