CryptGPU: Fast Privacy-Preserving Machine Learning on the GPU

22 April 2021

Papers citing "CryptGPU: Fast Privacy-Preserving Machine Learning on the GPU"

23 / 73 papers shown

Title
NFGen: Automatic Non-linear Function Evaluation Code Generator for General-purpose MPC Platforms Xiaoyu Fan Kun Chen Guosai Wang Mingchun Zhuang Yi Li Wei Xu 71 13 0 18 Oct 2022
Bicoptor: Two-round Secure Three-party Non-linear Computation without Preprocessing for Privacy-preserving Machine Learning Lijing Zhou Ziyu Wang Hongrui Cui Qingrui Song Yu Yu 113 13 0 05 Oct 2022
MPC-Pipe: an Efficient Pipeline Scheme for Secure Multi-party Machine Learning Inference Yongqin Wang Rachit Rajat Murali Annavaram 51 2 0 27 Sep 2022
PolyMPCNet: Towards ReLU-free Neural Architecture Search in Two-party Computation Based Private Inference Hongwu Peng Shangli Zhou Yukui Luo Shijin Duan Nuo Xu ... Tong Geng Ang Li Wujie Wen Xiaolin Xu Caiwen Ding 80 4 0 20 Sep 2022
OblivGM: Oblivious Attributed Subgraph Matching as a Cloud Service Songlei Wang Yifeng Zheng Xiaohua Jia Hejiao Huang Cong Wang 112 14 0 08 Sep 2022
Joint Linear and Nonlinear Computation across Functions for Efficient Privacy-Preserving Neural Network Inference Qiao Zhang Tao Xiang Chunsheng Xin Biwen Chen Hongyi Wu 111 1 0 04 Sep 2022
Private, Efficient, and Accurate: Protecting Models Trained by Multi-party Learning with Differential Privacy Wenqiang Ruan Ming Xu Wenjing Fang Li Wang Lei Wang Wei Han 81 14 0 18 Aug 2022
Privacy-Preserving Federated Recurrent Neural Networks Sinem Sav Abdulrahman Diaa Apostolos Pyrgelis Jean-Philippe Bossuat Jean-Pierre Hubaux FedML 101 8 0 28 Jul 2022
Characterizing and Optimizing End-to-End Systems for Private Inference Karthik Garimella Zahra Ghodsi N. Jha S. Garg Brandon Reagen 80 25 0 14 Jul 2022
Privacy-Preserving Analytics on Decentralized Social Graphs: The Case of Eigendecomposition Songlei Wang Yifeng Zheng Xiaohua Jia X. Yi 52 12 0 19 Jun 2022
Confidential Machine Learning within Graphcore IPUs K. Vaswani Stavros Volos Cédric Fournet Antonio Nino Diaz Ken Gordon ... D. Chisnall Saurabh Kulkarni Graham Cunningham Richard Osborne Dan C. Wilkinson 55 6 0 18 May 2022
Enabling All In-Edge Deep Learning: A Literature Review Praveen Joshi Mohammed Hasanuzzaman Chandra Thapa Haithem Afli T. Scully 100 24 0 07 Apr 2022
IncShrink: Architecting Efficient Outsourced Databases using Incremental MPC and Differential Privacy Chenghong Wang Johes Bater Kartik Nayak Ashwin Machanavajjhala 71 20 0 09 Mar 2022
SecGNN: Privacy-Preserving Graph Neural Network Training and Inference as a Cloud Service Songlei Wang Yifeng Zheng Xiaohua Jia GNN 102 25 0 16 Feb 2022
CryptoNite: Revealing the Pitfalls of End-to-End Private Inference at Scale Karthik Garimella N. Jha Zahra Ghodsi S. Garg Brandon Reagen 72 3 0 04 Nov 2021
Optimizing Secure Decision Tree Inference Outsourcing Yifeng Zheng Cong Wang Ruochen Wang Huayi Duan Surya Nepal 65 6 0 31 Oct 2021
Morse-STF: Improved Protocols for Privacy-Preserving Machine Learning Qizhi Zhang Sijun Tan Lichun Li Yun Zhao Dong Yin Shan Yin 33 1 0 24 Sep 2021
CrypTen: Secure Multi-Party Computation Meets Machine Learning Brian Knott Shobha Venkataraman Awni Y. Hannun Shubho Sengupta Mark Ibrahim Laurens van der Maaten 116 365 0 02 Sep 2021
Privacy-Preserving Machine Learning: Methods, Challenges and Directions Runhua Xu Nathalie Baracaldo J. Joshi 88 105 0 10 Aug 2021
Secure Quantized Training for Deep Learning Marcel Keller Ke Sun MQ 59 68 0 01 Jul 2021
Circa: Stochastic ReLUs for Private Deep Learning Zahra Ghodsi N. Jha Brandon Reagen S. Garg 71 34 0 15 Jun 2021
Adam in Private: Secure and Fast Training of Deep Neural Networks with Adaptive Moment Estimation Nuttapong Attrapadung Koki Hamada Dai Ikarashi Ryo Kikuchi Takahiro Matsuda Ibuki Mishina Hiraku Morita Jacob C. N. Schuldt 57 27 0 04 Jun 2021
SoK: Training Machine Learning Models over Multiple Sources with Privacy Preservation Lushan Song Guopeng Lin Jiaxuan Wang Haoqi Wu Wenqiang Ruan Weili Han 155 9 0 06 Dec 2020