Bridging ML and Threat Landscapes: Inference Attacks and Cryptographic Defenses for Training-Phase Data Protection
Machine learning systems use sensitive personal data to train and infer models, but developers are largely unaware of privacy attack vectors that evade conventional data security controls. This paper surveys the privacy threat landscape inherent to ML workflows, including membership inference attacks, model inversion a...