Securing Scalable AI Workloads in the Cloud: Architectural Considerations for Data Privacy and Governance

Abstract

The fast growth of AI workloads in the cloud has brought forth complex issues in the form of data privacy, governance, and secure scale. In this paper, we introduce a holistic architectural solution to AI system security throughout the whole lifecycle, including data ingestion, training, inference and deployment.