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Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning

5 December 2019

Harsh Chaudhari

Rahul Rachuri

Ajith Suresh

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Papers citing "Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning"

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Title
Comet: Accelerating Private Inference for Large Language Model by Predicting Activation Sparsity Guang Yan Yuhui Zhang Zimu Guo Lutan Zhao Xiaojun Chen Chen Wang Wenhao Wang Dan Meng Rui Hou 74 0 0 12 May 2025
The Communication-Friendly Privacy-Preserving Machine Learning against Malicious Adversaries Tianpei Lu Bingsheng Zhang Lichun Li Kui Ren 28 0 0 14 Nov 2024
Investigating Privacy Attacks in the Gray-Box Setting to Enhance Collaborative Learning Schemes Federico Mazzone Ahmad Al Badawi Y. Polyakov Maarten Everts Florian Hahn Andreas Peter MIACV AAML 66 0 0 25 Sep 2024
CryptoTrain: Fast Secure Training on Encrypted Dataset Jiaqi Xue Yancheng Zhang YanShan Wang Xueqiang Wang Hao Zheng Qian Lou 63 3 0 25 Sep 2024
Privacy-Preserving and Trustworthy Deep Learning for Medical Imaging Kiarash Sedghighadikolaei Attila A Yavuz 56 2 0 29 Jun 2024
SSNet: A Lightweight Multi-Party Computation Scheme for Practical Privacy-Preserving Machine Learning Service in the Cloud Shijin Duan Chenghong Wang Hongwu Peng Yukui Luo Wujie Wen Caiwen Ding Xiaolin Xu 58 5 0 04 Jun 2024
Pencil: Private and Extensible Collaborative Learning without the Non-Colluding Assumption Xuanqi Liu Zhuotao Liu Qi Li Ke Xu Mingwei Xu 63 8 0 17 Mar 2024
Wildest Dreams: Reproducible Research in Privacy-preserving Neural Network Training Tanveer Khan Mindaugas Budzys Khoa Nguyen A. Michalas 64 3 0 06 Mar 2024
How to Privately Tune Hyperparameters in Federated Learning? Insights from a Benchmark Study Natalija Mitic Apostolos Pyrgelis Sinem Sav FedML 91 1 0 25 Feb 2024
Spin: An Efficient Secure Computation Framework with GPU Acceleration Wuxuan Jiang Xiangjun Song Shenbai Hong Haijun Zhang Wenxin Liu Bo Zhao Wei Xu Yi Li 43 1 0 04 Feb 2024
Bicoptor 2.0: Addressing Challenges in Probabilistic Truncation for Enhanced Privacy-Preserving Machine Learning Lijing Zhou Qingrui Song Su Zhang Ziyu Wang Xianggui Wang Yong-Lu Li 64 4 0 10 Sep 2023
Approximating ReLU on a Reduced Ring for Efficient MPC-based Private Inference Kiwan Maeng G. E. Suh 47 2 0 09 Sep 2023
Integrating Homomorphic Encryption and Trusted Execution Technology for Autonomous and Confidential Model Refining in Cloud Pinglan Liu Wensheng Zhang 45 0 0 02 Aug 2023
ExTRUST: Reducing Exploit Stockpiles with a Privacy-Preserving Depletion System for Inter-State Relationships Thomas Reinhold Philip D. . Kuehn Daniel Gunther T. Schneider Christian A. Reuter 36 1 0 01 Jun 2023
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy Yifei Zhang Dun Zeng Jinglong Luo Zenglin Xu Irwin King FedML 156 49 0 21 Feb 2023
WW-FL: Secure and Private Large-Scale Federated Learning F. Marx T. Schneider Ajith Suresh Tobias Wehrle Christian Weinert Hossein Yalame FedML 51 2 0 20 Feb 2023
Private Multiparty Perception for Navigation Hui Lu Mia Chiquier Carl Vondrick EgoV 58 0 0 02 Dec 2022
ScionFL: Efficient and Robust Secure Quantized Aggregation Y. Ben-Itzhak Helen Mollering Benny Pinkas T. Schneider Ajith Suresh Oleksandr Tkachenko S. Vargaftik Christian Weinert Hossein Yalame Avishay Yanai 64 7 0 13 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 100 13 0 05 Oct 2022
pMPL: A Robust Multi-Party Learning Framework with a Privileged Party Lushan Song Jiaxuan Wang Zhexuan Wang Xinyu Tu Guopeng Lin Wenqiang Ruan Haoqi Wu Wei Han 66 18 0 02 Oct 2022
Privacy-Preserving Federated Recurrent Neural Networks Sinem Sav Abdulrahman Diaa Apostolos Pyrgelis Jean-Philippe Bossuat Jean-Pierre Hubaux FedML 83 8 0 28 Jul 2022
Hercules: Boosting the Performance of Privacy-preserving Federated Learning Guowen Xu Xingshuo Han Shengmin Xu Tianwei Zhang Hongwei Li Xinyi Huang R. Deng FedML 113 16 0 11 Jul 2022
Privacy-preserving Decentralized Deep Learning with Multiparty Homomorphic Encryption Guowen Xu Guanlin Li Shangwei Guo Tianwei Zhang Hongwei Li FedML 52 3 0 11 Jul 2022
MPClan: Protocol Suite for Privacy-Conscious Computations Nishat Koti S. Patil A. Patra Ajith Suresh 49 18 0 24 Jun 2022
Towards Practical Privacy-Preserving Solution for Outsourced Neural Network Inference Pinglan Liu Wensheng Zhang FedML 21 3 0 06 Jun 2022
Privacy-Preserving Epidemiological Modeling on Mobile Graphs Daniel Gunther Marco Holz B. Judkewitz Helen Mollering Benny Pinkas T. Schneider Ajith Suresh 98 4 0 01 Jun 2022
SafeNet: The Unreasonable Effectiveness of Ensembles in Private Collaborative Learning Harsh Chaudhari Matthew Jagielski Alina Oprea 72 7 0 20 May 2022
Fusion: Efficient and Secure Inference Resilient to Malicious Servers Caiqin Dong Jian Weng Jia-Nan Liu Yue Zhang Yao Tong Anjia Yang Yudan Cheng Shun Hu 65 16 0 06 May 2022
SPIKE: Secure and Private Investigation of the Kidney Exchange problem T. Birka K. Hamacher Tobias Kussel Helen Mollering T. Schneider 16 4 0 21 Apr 2022
Towards Privacy-Preserving and Verifiable Federated Matrix Factorization Xicheng Wan Yifeng Zheng Qun Li Anmin Fu Mang Su Yan Gao 34 9 0 04 Apr 2022
Efficient Dropout-resilient Aggregation for Privacy-preserving Machine Learning Ziyao Liu Jiale Guo Kwok-Yan Lam Jun Zhao 65 82 0 31 Mar 2022
Privacy-Preserving Aggregation in Federated Learning: A Survey Ziyao Liu Jiale Guo Wenzhuo Yang Jiani Fan Kwok-Yan Lam Jun Zhao FedML 100 93 0 31 Mar 2022
ABG: A Multi-Party Mixed Protocol Framework for Privacy-Preserving Cooperative Learning Hao Wang Zhi Li Chunpeng Ge W. Susilo FedML 32 0 0 07 Feb 2022
More is Merrier: Relax the Non-Collusion Assumption in Multi-Server PIR Tiantian Gong Ryan Henry Alexandros Psomas Aniket Kate 15 3 0 19 Jan 2022
CryptoNite: Revealing the Pitfalls of End-to-End Private Inference at Scale Karthik Garimella N. Jha Zahra Ghodsi S. Garg Brandon Reagen 70 3 0 04 Nov 2021
Optimizing Secure Decision Tree Inference Outsourcing Yifeng Zheng Cong Wang Ruochen Wang Huayi Duan Surya Nepal 63 6 0 31 Oct 2021
CrypTen: Secure Multi-Party Computation Meets Machine Learning Brian Knott Shobha Venkataraman Awni Y. Hannun Shubho Sengupta Mark Ibrahim Laurens van der Maaten 102 364 0 02 Sep 2021
Towards Secure and Practical Machine Learning via Secret Sharing and Random Permutation Fei Zheng Chaochao Chen Xiaolin Zheng Mingjie Zhu FedML 40 21 0 17 Aug 2021
Sisyphus: A Cautionary Tale of Using Low-Degree Polynomial Activations in Privacy-Preserving Deep Learning Karthik Garimella N. Jha Brandon Reagen 85 19 0 26 Jul 2021
Tetrad: Actively Secure 4PC for Secure Training and Inference Nishat Koti A. Patra Rahul Rachuri Ajith Suresh 70 72 0 05 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 52 27 0 04 Jun 2021
CryptGPU: Fast Privacy-Preserving Machine Learning on the GPU Sijun Tan Brian Knott Yuan Tian David J. Wu BDL FedML 106 193 0 22 Apr 2021
Practical Two-party Privacy-preserving Neural Network Based on Secret Sharing ZhengQiang Ge Zhipeng Zhou Dong Guo Qiang Li FedML 31 5 0 10 Apr 2021
Privacy-Preserving Video Classification with Convolutional Neural Networks Sikha Pentyala Rafael Dowsley Martine De Cock PICV 95 21 0 06 Feb 2021
Secrecy: Secure collaborative analytics on secret-shared data J. Liagouris Vasiliki Kalavri Muhammad Faisal Mayank Varia 54 19 0 01 Feb 2021
SoK: Training Machine Learning Models over Multiple Sources with Privacy Preservation Lushan Song Guopeng Lin Jiaxuan Wang Haoqi Wu Wenqiang Ruan Weili Han 142 9 0 06 Dec 2020
Effectiveness of MPC-friendly Softmax Replacement Marcel Keller Ke Sun 27 10 0 23 Nov 2020
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 47 156 0 01 Sep 2020
ARIANN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing T. Ryffel Pierre Tholoniat D. Pointcheval Francis R. Bach FedML 157 100 0 08 Jun 2020
SWIFT: Super-fast and Robust Privacy-Preserving Machine Learning Nishat Koti Mahak Pancholi A. Patra Ajith Suresh 83 146 0 20 May 2020