PrivFT: Private and Fast Text Classification with Homomorphic Encryption

19 August 2019

Papers citing "PrivFT: Private and Fast Text Classification with Homomorphic Encryption"

9 / 9 papers shown

Title
Encryption-Friendly LLM Architecture Donghwan Rho Taeseong Kim Minje Park Jung Woo Kim Hyunsik Chae Jung Hee Cheon Ernest K. Ryu 54 2 0 24 Feb 2025
HETAL: Efficient Privacy-preserving Transfer Learning with Homomorphic Encryption Seewoo Lee Garam Lee Jung Woo Kim Junbum Shin Mun-Kyu Lee 33 25 0 21 Mar 2024
REED: Chiplet-Based Accelerator for Fully Homomorphic Encryption Aikata Aikata A. Mert Sunmin Kwon M. Deryabin S. Roy 100 2 0 05 Aug 2023
TensorFHE: Achieving Practical Computation on Encrypted Data Using GPGPU Shengyu Fan Zhiwei Wang Weizhi Xu Rui Hou Dan Meng M. Zhang FedML 17 44 0 29 Dec 2022
Medha: Microcoded Hardware Accelerator for computing on Encrypted Data A. Mert Sunmin Aikata Sunmin Kwon Youngsam Shin Donghoon Yoo Yongwoo Yoo Sinha Roy 29 34 0 11 Oct 2022
Verifiable Encodings for Secure Homomorphic Analytics Sylvain Chatel Christian Knabenhans Apostolos Pyrgelis Carmela Troncoso Jean-Pierre Hubaux 23 19 0 28 Jul 2022
SoK: Privacy Preserving Machine Learning using Functional Encryption: Opportunities and Challenges Prajwal Panzade Daniel Takabi 14 6 0 11 Apr 2022
BTS: An Accelerator for Bootstrappable Fully Homomorphic Encryption Sangpyo Kim Jongmin Kim M. Kim Wonkyung Jung Minsoo Rhu John Kim Jung Ho Ahn 13 136 0 31 Dec 2021
POSEIDON: Privacy-Preserving Federated Neural Network Learning Sinem Sav Apostolos Pyrgelis J. Troncoso-Pastoriza D. Froelicher Jean-Philippe Bossuat João Sá Sousa Jean-Pierre Hubaux FedML 11 153 0 01 Sep 2020