ASTRA: High Throughput 3PC over Rings with Application to Secure Prediction

5 December 2019

Ajith Suresh

Papers citing "ASTRA: High Throughput 3PC over Rings with Application to Secure Prediction"

32 / 32 papers shown

Title
The Communication-Friendly Privacy-Preserving Machine Learning against Malicious Adversaries Tianpei Lu Bingsheng Zhang Lichun Li Kui Ren 28 0 0 14 Nov 2024
Online Efficient Secure Logistic Regression based on Function Secret Sharing Jing Liu Jamie Cui Cen Chen 36 5 0 18 Sep 2023
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 67 4 0 10 Sep 2023
Approximating ReLU on a Reduced Ring for Efficient MPC-based Private Inference Kiwan Maeng G. E. Suh 52 2 0 09 Sep 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 41 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 60 2 0 20 Feb 2023
Efficient Privacy-Preserving Machine Learning with Lightweight Trusted Hardware Pengzhi Huang Thang Hoang Yueying Li Elaine Shi G. E. Suh 55 3 0 18 Oct 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 102 13 0 05 Oct 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
MPClan: Protocol Suite for Privacy-Conscious Computations Nishat Koti S. Patil A. Patra Ajith Suresh 49 18 0 24 Jun 2022
Privacy-Preserving Epidemiological Modeling on Mobile Graphs Daniel Gunther Marco Holz B. Judkewitz Helen Mollering Benny Pinkas T. Schneider Ajith Suresh 100 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
SPIKE: Secure and Private Investigation of the Kidney Exchange problem T. Birka K. Hamacher Tobias Kussel Helen Mollering T. Schneider 21 4 0 21 Apr 2022
SecGNN: Privacy-Preserving Graph Neural Network Training and Inference as a Cloud Service Songlei Wang Yifeng Zheng Xiaohua Jia GNN 90 25 0 16 Feb 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
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
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 137 16 0 20 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 110 364 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 92 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 57 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
Secrecy: Secure collaborative analytics on secret-shared data J. Liagouris Vasiliki Kalavri Muhammad Faisal Mayank Varia 57 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 145 9 0 06 Dec 2020
SWIFT: Super-fast and Robust Privacy-Preserving Machine Learning Nishat Koti Mahak Pancholi A. Patra Ajith Suresh 83 146 0 20 May 2020
BLAZE: Blazing Fast Privacy-Preserving Machine Learning A. Patra Ajith Suresh 75 200 0 18 May 2020
FALCON: Honest-Majority Maliciously Secure Framework for Private Deep Learning Sameer Wagh Shruti Tople Fabrice Benhamouda E. Kushilevitz Prateek Mittal T. Rabin FedML 95 303 0 05 Apr 2020
Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning Harsh Chaudhari Rahul Rachuri Ajith Suresh 108 214 0 05 Dec 2019
CrypTFlow: Secure TensorFlow Inference Nishant Kumar Mayank Rathee Nishanth Chandran Divya Gupta Aseem Rastogi Rahul Sharma 156 244 0 16 Sep 2019