CryptoSPN
Amos Treiber, Alejandro Molina, Christian Weinert, Thomas H. Schneider, Kristian Kersting · 2020
The ubiquitous deployment of machine learning (ML) technologies has certainly improved many applications but also raised challenging privacy concerns, as sensitive client data is usually processed remotely at the discretion of a service provider. Therefore, privacy-preserving machine learning (PPML) aims at providing privacy using techniques such as secure multi-party computation (SMPC).