Is Private Learning Possible with Instance Encoding?

10 November 2020

Papers citing "Is Private Learning Possible with Instance Encoding?"

23 / 23 papers shown

Title
Adaptive Hybrid Masking Strategy for Privacy-Preserving Face Recognition Against Model Inversion Attack Yinggui Wang Yuanqing Huang Jianshu Li Le Yang Kai Song Lei Wang AAML PICV 56 0 0 14 Mar 2024
Approximating ReLU on a Reduced Ring for Efficient MPC-based Private Inference Kiwan Maeng G. E. Suh 30 2 0 09 Sep 2023
Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information Kiwan Maeng Chuan Guo Sanjay Kariyappa G. E. Suh 21 8 0 06 May 2023
PEOPL: Characterizing Privately Encoded Open Datasets with Public Labels H. Esfahanizadeh Adam Yala Rafael G. L. DÓliveira Andrea J. D. Jaba Victor Quach ... Tommi Jaakkola Vinod Vaikuntanathan M. Ghobadi Regina Barzilay Muriel Médard 25 0 0 31 Mar 2023
Privacy-Preserving Face Recognition with Learnable Privacy Budgets in Frequency Domain Jia-Bao Ji Huan Wang Y. Huang Jiaxiang Wu Xingkun Xu Shouhong Ding Shengchuan Zhang Liujuan Cao Rongrong Ji CVBM PICV 57 35 0 15 Jul 2022
DarKnight: An Accelerated Framework for Privacy and Integrity Preserving Deep Learning Using Trusted Hardware H. Hashemi Yongqin Wang M. Annavaram FedML 26 58 0 30 Jun 2022
Enhancing Privacy against Inversion Attacks in Federated Learning by using Mixing Gradients Strategies Shaltiel Eloul Fran Silavong Sanket Kamthe Antonios Georgiadis Sean J. Moran FedML 20 5 0 26 Apr 2022
Deep Unlearning via Randomized Conditionally Independent Hessians Ronak R. Mehta Sourav Pal Vikas Singh Sathya Ravi MU 27 81 0 15 Apr 2022
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning Yangsibo Huang Samyak Gupta Zhao Song Kai Li Sanjeev Arora FedML AAML SILM 31 269 0 30 Nov 2021
Practical and Secure Federated Recommendation with Personalized Masks Liu Yang Ben Tan Bo Liu V. Zheng Kun Guo Kai Chen Qiang Yang FedML 32 16 0 18 Aug 2021
Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates Steve Chien Prateek Jain Walid Krichene Steffen Rendle Shuang Song Abhradeep Thakurta Li Zhang 25 19 0 20 Jul 2021
Disrupting Model Training with Adversarial Shortcuts Ivan Evtimov Ian Covert Aditya Kusupati Tadayoshi Kohno AAML 28 10 0 12 Jun 2021
Differential Privacy for Text Analytics via Natural Text Sanitization Xiang Yue Minxin Du Tianhao Wang Yaliang Li Huan Sun Sherman S. M. Chow 24 84 0 02 Jun 2021
A Fusion-Denoising Attack on InstaHide with Data Augmentation Xinjian Luo X. Xiao Yuncheng Wu Juncheng Liu Beng Chin Ooi FedML PICV 52 7 0 17 May 2021
Privacy and Integrity Preserving Training Using Trusted Hardware H. Hashemi Yongqin Wang M. Annavaram FedML 16 0 0 01 May 2021
DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation Wei Ping Fan Wu Yunhui Long Luka Rimanic Ce Zhang Bo-wen Li FedML 45 63 0 20 Mar 2021
Defending Medical Image Diagnostics against Privacy Attacks using Generative Methods William Paul Yinzhi Cao Miaomiao Zhang Philippe Burlina AAML MedIm 26 15 0 04 Mar 2021
DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations Eitan Borgnia Jonas Geiping Valeriia Cherepanova Liam H. Fowl Arjun Gupta Amin Ghiasi Furong Huang Micah Goldblum Tom Goldstein 37 46 0 02 Mar 2021
Symmetric Sparse Boolean Matrix Factorization and Applications Sitan Chen Zhao Song Runzhou Tao Ruizhe Zhang 41 5 0 02 Feb 2021
InstaHide's Sample Complexity When Mixing Two Private Images Baihe Huang Zhao Song Runzhou Tao Junze Yin Ruizhe Zhang Danyang Zhuo MIACV 28 9 0 24 Nov 2020
On InstaHide, Phase Retrieval, and Sparse Matrix Factorization Sitan Chen Xiaoxiao Li Zhao Song Danyang Zhuo 27 13 0 23 Nov 2020
Synthetic Data -- Anonymisation Groundhog Day Theresa Stadler Bristena Oprisanu Carmela Troncoso 13 156 0 13 Nov 2020
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning Xinjian Luo Xiangqi Zhu FedML 73 25 0 27 Apr 2020