Privacy and Security Implications of Cloud-Based AI Services : A Survey

This paper details the privacy and security landscape in today's cloud ecosystem and identifies that there is a gap in addressing the risks introduced by machine learning models. As machine learning algorithms continue to evolve and find applications across diverse domains, the need to categorize and quantify privacy and security risks becomes increasingly critical. With the emerging trend of AI-as-a-Service (AIaaS), machine learned AI models (or ML models) are deployed on the cloud by model providers and used by model …

ai services algorithms applications cloud cloud-based cs.ai cs.cr cs.lg diverse domains ecosystem gap landscape machine machine learning machine learning algorithms machine learning models paper privacy privacy and security risks security services survey