Session

Smart Vehicles, Secure Data: Recreating Vehicle Environments for Privacy-Preserving Machine Learning

Overview

ExperienceIn Person
TypeBreakout
TrackArtificial Intelligence
IndustryEnterprise Technology
TechnologiesApache Spark, AI/BI, Databricks Workflows
Skill LevelIntermediate
Duration40 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