Session
Smart Vehicles, Secure Data: Recreating Vehicle Environments for Privacy-Preserving Machine Learning
Overview
Experience | In Person |
---|---|
Type | Breakout |
Track | Artificial Intelligence |
Industry | Enterprise Technology |
Technologies | Apache Spark, AI/BI, Databricks Workflows |
Skill Level | Intermediate |
Duration | 40 min |
As connected vehicles generate vast amounts of personal and sensitive data, ensuring privacy and security in machine learning (ML) processes is essential. This session explores how Trusted Execution Environments (TEEs) and Azure Confidential Computing can enable privacy-preserving ML in cloud environments. We’ll present a method to recreate a vehicle environment in the cloud, where sensitive data remains private throughout model training, inference and deployment. Attendees will learn how Mercedes-Benz R&D North America builds secure, privacy-respecting personalized systems for the next generation of connected vehicles.
Session Speakers
Frankie Cancino
/Senior Data Scientist
Mercedes-Benz R&D