“Linear-complexity private function evaluation is practical” by Marco Holz, Ágnes Kiss, Deevashwer Rathee, and Thomas Schneider was accepted at ESORICS'20.

Watch our explanatory video on private set intersection (PSI) with applications to privacy-preserving mobile contact discovery.

“MP2ML: A mixed-protocol machine learning framework for private inference” by Fabian Boemer, Rosario Cammarota, Daniel Demmler, Thomas Schneider, and Hossein Yalame was accepted at ARES'20.

Thomas Schneider is program committee member of WPES'20.

Thomas Schneider is program committee member of ACM CCSW'20.

Amos Treiber will give a contributed talk on “CryptoSPN: Privacy-preserving Machine Learning beyond Neural Networks” at TPMPC'20

Thomas Schneider is program committee member of NDSS'21.

“Secure two-party computation in a post-quantum world” by Niklas Büscher, Daniel Demmler, Nikolaos P. Karvelas, Stefan Katzenbeisser, Juliane Krämer, Deevashwer Rathee, Thomas Schneider, and Patrick Struck was accepted at 18. International Conference on Applied Cryptography and Network Security (ACNS'20).

Why do we need and how to enable privacy-preserving face recognition? Thomas Schneider gives an answer in the new hr-info podcast.

“Small Constant Mean-Error Imprecise Adder/Multiplier for Efficient VLSI Implementation of MAC-based Applications” by Mohammad Javadi, Hossein Yalame, and Hamid Reza Mahdiani was accepted at Transactions on Computers .