FLUENT: A Tool for Efficient Mixed-Protocol Semi-Private Function Evaluation

D Günther, J Schmidt, T Schneider… - Cryptology ePrint …, 2024‏ - eprint.iacr.org
In modern business to customer interactions, handling private or confidential data is
essential. Private Function Evaluation (PFE) protocols ensure the privacy of both the …

Truncation Untangled: Scaling Fixed-Point Arithmetic for Privacy-Preserving Machine Learning to Large Models and Datasets

C Harth-Kitzerow, G Carle - Cryptology ePrint Archive, 2024‏ - eprint.iacr.org
Fixed point arithmetic (FPA) is essential to enable practical Privacy-Preserving Machine
Learning. When multiplying two fixed-point numbers, truncation is required to ensure that the …

PIGEON: A Framework for Private Inference of Neural Networks

C Harth-Kitzerow, Y Wang, R Rajat, G Carle… - Cryptology ePrint …, 2024‏ - eprint.iacr.org
Abstract Privacy-Preserving Machine Learning is one of the most relevant use cases for
Secure Multiparty Computation (MPC). While private training of large neural networks such …