We present CrypTFlow2, a cryptographic framework for secure inference over realistic Deep Neural Networks (DNNs) using secure. 2-party computation. CrypTFlow2 ...
Oct 13, 2020 · Abstract:We present CrypTFlow2, a cryptographic framework for secure inference over realistic Deep Neural Networks (DNNs) using secure ...
Nov 2, 2020 · Abstract. We present CrypTFlow2, a cryptographic framework for secure inference over realistic Deep Neural Networks (DNNs) using secure 2-party ...
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Recently, it is required that machine learning / neural networks be secure. • Using garbled circuits enable ML/NN secure but its communication cost is large.
Using CrypTFlow2, the first secure inference over ImageNet-scale DNNs like ResNet50 and DenseNet121 is presented, at least an order of magnitude larger than ...
CrypTFlow2 [16] proposes a new secure comparison and division protocol based on homomorphic encryption. They have carefully designed the secure inference task ...
SCI (part of CrypTFlow2, SIRNN, SecFloat, and Beacon): a semi-honest 2-party computation library for secure (fixed-point) inference on deep neural networks and ...
CrypTFlow2: Practical 2-Party Secure Inference - Academia.edu
www.academia.edu › CrypTFlow2_Practi...
We design, implement, and evaluate DELPHI, a secure prediction system that allows two parties to execute neural network inference without revealing either ...
May 27, 2022 · https://www.youtube.com/watch?v=WicRo6SLpCQ&t=2360sCrypTFlow2: Practical 2-Party Secure Inference, by Deevashwer Rathee Mayank Rathee ...