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Privacy Side Channels in Machine Learning Systems

Most current approaches for protecting privacy in machine learning (ML) assume that models exist in a vacuum, when in reality, ML …

Edoardo Debenedetti, Giorgio Severi, Nicholas Carlini, Christopher A. Choquette-Choo, Matthew Jagielski, Milad Nasr, Eric Wallace, Florian Tramèr