Gazelle: A Low Latency Framework for Secure Neural Network Inference

16 January 2018

Papers citing "Gazelle: A Low Latency Framework for Secure Neural Network Inference"

50 / 311 papers shown

Title
Efficient CNN Building Blocks for Encrypted Data Nayna Jain Karthik Nandakumar Nalini Ratha Sharath Pankanti U. Kumar FedML 63 14 0 30 Jan 2021
S++: A Fast and Deployable Secure-Computation Framework for Privacy-Preserving Neural Network Training Prashanthi Ramachandran Shivam Agarwal A. Mondal Aastha Shah Debayan Gupta FedML 36 9 0 28 Jan 2021
Reducing ReLU Count for Privacy-Preserving CNN Speedup Inbar Helbitz S. Avidan 33 4 0 28 Jan 2021
secureTF: A Secure TensorFlow Framework D. Quoc Franz Gregor Sergei Arnautov Roland Kunkel Pramod Bhatotia Christof Fetzer 93 40 0 20 Jan 2021
Porcupine: A Synthesizing Compiler for Vectorized Homomorphic Encryption M. Cowan Deeksha Dangwal Armin Alaghi Caroline Trippel Vincent T. Lee Brandon Reagen 25 37 0 19 Jan 2021
Fast Privacy-Preserving Text Classification based on Secure Multiparty Computation A. Resende Davis Railsback Rafael Dowsley Anderson C. A. Nascimento Diego F. Aranha 55 21 0 18 Jan 2021
SoK: Fully Homomorphic Encryption Compilers Alexander Viand Patrick Jattke Anwar Hithnawi 75 99 0 18 Jan 2021
Neural Network Training With Homomorphic Encryption Kentaro Mihara Ryohei Yamaguchi M. Mitsuishi Y. Maruyama 29 7 0 25 Dec 2020
DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for deep neural networks Abhishek Singh Ayush Chopra Vivek Sharma Ethan Garza Emily Zhang Praneeth Vepakomma Ramesh Raskar 52 46 0 20 Dec 2020
FedServing: A Federated Prediction Serving Framework Based on Incentive Mechanism Jiasi Weng Jian Weng Hongwei Huang Chengjun Cai Cong Wang FedML 57 28 0 19 Dec 2020
Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design Jun Zhou Longfei Zheng Chaochao Chen Yan Wang Xiaolin Zheng Bingzhe Wu Cen Chen Li Wang Jianwei Yin FedML 61 3 0 17 Dec 2020
Secure Medical Image Analysis with CrypTFlow Javier Alvarez-Valle Pratik Bhatu Nishanth Chandran Divya Gupta A. Nori Aseem Rastogi Mayank Rathee Rahul Sharma Shubham Ugare MedIm 66 13 0 09 Dec 2020
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
Customizing Trusted AI Accelerators for Efficient Privacy-Preserving Machine Learning Peichen Xie Xuanle Ren Guangyu Sun FedML 32 6 0 12 Nov 2020
ShadowNet: A Secure and Efficient On-device Model Inference System for Convolutional Neural Networks Zhichuang Sun Ruimin Sun Changming Liu A. Chowdhury Long Lu S. Jha FedML 105 20 0 11 Nov 2020
Privacy-Preserving XGBoost Inference Xianrui Meng J. Feigenbaum 62 14 0 09 Nov 2020
HeLayers: A Tile Tensors Framework for Large Neural Networks on Encrypted Data E. Aharoni Allon Adir Moran Baruch Nir Drucker Gilad Ezov ... Ramy Masalha Guy Moshkowich Dov Murik Hayim Shaul Omri Soceanu FedML 119 58 0 03 Nov 2020
CryptoGRU: Low Latency Privacy-Preserving Text Analysis With GRU Bo Feng Qian Lou Lei Jiang Geoffrey C. Fox 62 15 0 22 Oct 2020
CrypTFlow2: Practical 2-Party Secure Inference Deevashwer Rathee Mayank Rathee Nishant Kumar Nishanth Chandran Divya Gupta Aseem Rastogi Rahul Sharma 139 316 0 13 Oct 2020
STR: Secure Computation on Additive Shares Using the Share-Transform-Reveal Strategy Zhihua Xia Qi Gu Wenhao Zhou Lizhi Xiong J. Weng Neal N. Xiong 51 0 0 28 Sep 2020
Privacy-Preserving Machine Learning Training in Aggregation Scenarios Liehuang Zhu Xiangyun Tang Meng Shen Jie Zhang Xiaojiang Du 54 4 0 21 Sep 2020
Privacy-Preserving Image Retrieval Based on Additive Secret Sharing Zhihua Xia Qi Gu Lizhi Xiong Wenhao Zhou J. Weng 13 8 0 15 Sep 2020
Accelerating 2PC-based ML with Limited Trusted Hardware M. Nawaz Aditya Gulati Kunlong Liu Vishwajeet Agrawal P. Ananth Trinabh Gupta 113 2 0 11 Sep 2020
Fairness in the Eyes of the Data: Certifying Machine-Learning Models Shahar Segal Yossi Adi Benny Pinkas Carsten Baum C. Ganesh Joseph Keshet FedML 59 37 0 03 Sep 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
Data-driven control on encrypted data A. Alexandru Anastasios Tsiamis George J. Pappas 43 6 0 28 Aug 2020
Efficient Private Machine Learning by Differentiable Random Transformations F. Zheng 16 0 0 18 Aug 2020
Key-Nets: Optical Transformation Convolutional Networks for Privacy Preserving Vision Sensors J. Byrne Brian DeCann S. Bloom PICV 29 5 0 11 Aug 2020
Trustworthy AI Inference Systems: An Industry Research View Rosario Cammarota M. Schunter Anand Rajan Fabian Boemer Ágnes Kiss ... Aydin Aysu Fateme S. Hosseini Chengmo Yang Eric Wallace Pam Norton 99 14 0 10 Aug 2020
VFL: A Verifiable Federated Learning with Privacy-Preserving for Big Data in Industrial IoT Anmin Fu Xianglong Zhang N. Xiong Yansong Gao Huaqun Wang FedML 55 183 0 27 Jul 2020
SOTERIA: In Search of Efficient Neural Networks for Private Inference Anshul Aggarwal Trevor E. Carlson Reza Shokri Shruti Tople FedML 44 11 0 25 Jul 2020
MPC-enabled Privacy-Preserving Neural Network Training against Malicious Attack Ziyao Liu Ivan Tjuawinata C. Xing K. Lam 60 9 0 24 Jul 2020
BUNET: Blind Medical Image Segmentation Based on Secure UNET S. Bian Xiaowei Xu Weiwen Jiang Yiyu Shi Takashi Sato 52 6 0 14 Jul 2020
Additively Homomorphical Encryption based Deep Neural Network for Asymmetrically Collaborative Machine Learning Yifei Zhang Hao Zhu FedML 56 42 0 14 Jul 2020
Privacy and Integrity Preserving Computations with CRISP Sylvain Chatel Apostolos Pyrgelis J. Troncoso-Pastoriza Jean-Pierre Hubaux 34 9 0 08 Jul 2020
Offline Model Guard: Secure and Private ML on Mobile Devices Sebastian P. Bayerl Tommaso Frassetto Patrick Jauernig Korbinian Riedhammer A. Sadeghi T. Schneider Emmanuel Stapf Christian Weinert OffRL 67 45 0 05 Jul 2020
Private Speech Classification with Secure Multiparty Computation Kyle Bittner Martine De Cock Rafael Dowsley 45 1 0 01 Jul 2020
Rotation-Equivariant Neural Networks for Privacy Protection Hao Zhang Yiting Chen Haotian Ma Xu Cheng Qihan Ren Liyao Xiang Jie Shi Quanshi Zhang 27 3 0 21 Jun 2020
Faster Secure Data Mining via Distributed Homomorphic Encryption Junyi Li Heng-Chiao Huang FedML 67 21 0 17 Jun 2020
Visor: Privacy-Preserving Video Analytics as a Cloud Service Rishabh Poddar Ganesh Ananthanarayanan Srinath T. V. Setty Stavros Volos Raluca A. Popa 69 64 0 17 Jun 2020
BoMaNet: Boolean Masking of an Entire Neural Network Anuj Dubey Rosario Cammarota Aydin Aysu AAML 71 46 0 16 Jun 2020
SPEED: Secure, PrivatE, and Efficient Deep learning Arnaud Grivet Sébert Rafael Pinot Martin Zuber Cédric Gouy-Pailler Renaud Sirdey FedML 55 20 0 16 Jun 2020
CryptoNAS: Private Inference on a ReLU Budget Zahra Ghodsi A. Veldanda Brandon Reagen S. Garg 87 87 0 15 Jun 2020
Secure Byzantine-Robust Machine Learning Lie He Sai Praneeth Karimireddy Martin Jaggi OOD 81 60 0 08 Jun 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
AutoPrivacy: Automated Layer-wise Parameter Selection for Secure Neural Network Inference Qian Lou B. Song Lei Jiang 71 36 0 07 Jun 2020
Secure Sum Outperforms Homomorphic Encryption in (Current) Collaborative Deep Learning Derian Boer Stefan Kramer FedML 63 8 0 02 Jun 2020
DarKnight: A Data Privacy Scheme for Training and Inference of Deep Neural Networks H. Hashemi Yongqin Wang M. Annavaram FedML 67 26 0 01 Jun 2020
Cheetah: Optimizing and Accelerating Homomorphic Encryption for Private Inference Brandon Reagen Wooseok Choi Yeongil Ko Vincent T. Lee Gu-Yeon Wei Hsien-Hsin S. Lee David Brooks 46 16 0 31 May 2020
Scalable Privacy-Preserving Distributed Learning D. Froelicher J. Troncoso-Pastoriza Apostolos Pyrgelis Sinem Sav João Sá Sousa Jean-Philippe Bossuat Jean-Pierre Hubaux FedML 84 70 0 19 May 2020