Deep Learning with Differential Privacy

1 July 2016

Papers citing "Deep Learning with Differential Privacy"

50 / 1,195 papers shown

Title
FedDPGAN: Federated Differentially Private Generative Adversarial Networks Framework for the Detection of COVID-19 Pneumonia Longling Zhang Bochen Shen A. Barnawi Shan Xi Neeraj Kumar Yi Wu FedML MedIm 83 80 0 26 Apr 2021
Wireless Federated Learning (WFL) for 6G Networks -- Part I: Research Challenges and Future Trends Pavlos S. Bouzinis P. Diamantoulakis G. Karagiannidis 29 50 0 24 Apr 2021
CryptGPU: Fast Privacy-Preserving Machine Learning on the GPU Sijun Tan Brian Knott Yuan Tian David J. Wu BDL FedML 57 186 0 22 Apr 2021
Membership Inference Attack Susceptibility of Clinical Language Models Abhyuday N. Jagannatha Bhanu Pratap Singh Rawat Hong-ye Yu MIACV 29 62 0 16 Apr 2021
Privacy-preserving Federated Learning based on Multi-key Homomorphic Encryption Jing Ma Si-Ahmed Naas S. Sigg X. Lyu 31 246 0 14 Apr 2021
Can Differential Privacy Practically Protect Collaborative Deep Learning Inference for the Internet of Things? Jihyeon Ryu Yifeng Zheng Yansong Gao A. Abuadbba Junyaup Kim Dongho Won Surya Nepal Hyoungshick Kim Cong Wang 26 12 0 08 Apr 2021
Distributed Learning in Wireless Networks: Recent Progress and Future Challenges Mingzhe Chen Deniz Gündüz Kaibin Huang Walid Saad M. Bennis Aneta Vulgarakis Feljan H. Vincent Poor 45 403 0 05 Apr 2021
Perceptual Indistinguishability-Net (PI-Net): Facial Image Obfuscation with Manipulable Semantics Jiawei Chen Li-ju Chen Chia-Mu Yu Chun-Shien Lu PICV 30 40 0 05 Apr 2021
Perun: Secure Multi-Stakeholder Machine Learning Framework with GPU Support W. Ożga D. Quoc Christof Fetzer FedML 28 4 0 31 Mar 2021
Privacy and Trust Redefined in Federated Machine Learning Pavlos Papadopoulos Will Abramson A. Hall Nikolaos Pitropakis William J. Buchanan 38 42 0 29 Mar 2021
Differentially Private Normalizing Flows for Privacy-Preserving Density Estimation Chris Waites Rachel Cummings 19 15 0 25 Mar 2021
Federated Quantum Machine Learning Samuel Yen-Chi Chen Shinjae Yoo FedML AI4CE 24 118 0 22 Mar 2021
DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation Wei Ping Fan Wu Yunhui Long Luka Rimanic Ce Zhang Yue Liu FedML 56 63 0 20 Mar 2021
Differentially private inference via noisy optimization Marco Avella-Medina Casey Bradshaw Po-Ling Loh FedML 49 29 0 19 Mar 2021
Quantum federated learning through blind quantum computing Weikang Li Sirui Lu D. Deng FedML 27 83 0 15 Mar 2021
Membership Inference Attacks on Machine Learning: A Survey Hongsheng Hu Z. Salcic Lichao Sun Gillian Dobbie Philip S. Yu Xuyun Zhang MIACV 42 413 0 14 Mar 2021
Privacy Regularization: Joint Privacy-Utility Optimization in Language Models Fatemehsadat Mireshghallah Huseyin A. Inan Marcello Hasegawa Victor Rühle Taylor Berg-Kirkpatrick Robert Sim 19 40 0 12 Mar 2021
Private Cross-Silo Federated Learning for Extracting Vaccine Adverse Event Mentions Pallika H. Kanani Virendra J. Marathe Daniel W. Peterson R. Harpaz Steve Bright FedML 21 9 0 12 Mar 2021
On the (In)Feasibility of Attribute Inference Attacks on Machine Learning Models Benjamin Zi Hao Zhao Aviral Agrawal Catisha Coburn Hassan Jameel Asghar Raghav Bhaskar M. Kâafar Darren Webb Peter Dickinson MIACV 37 38 0 12 Mar 2021
A Study of Face Obfuscation in ImageNet Kaiyu Yang Jacqueline Yau Li Fei-Fei Jia Deng Olga Russakovsky PICV CVBM 34 144 0 10 Mar 2021
NegDL: Privacy-Preserving Deep Learning Based on Negative Database Dongdong Zhao Pingchuan Zhang Jianwen Xiang Jing Tian SyDa 16 0 0 10 Mar 2021
IdentityDP: Differential Private Identification Protection for Face Images Yunqian Wen Li Song Bo Liu Ming Ding Rong Xie PICV 50 62 0 02 Mar 2021
$Private Stochastic Convex Optimization: Optimal Rates in $\ell_1$ Geometry$ Private Stochastic Convex Optimization: Optimal Rates in $\ell_1$ Geometry Hilal Asi Vitaly Feldman Tomer Koren Kunal Talwar 30 91 0 02 Mar 2021
Blockchain-Based Federated Learning in Mobile Edge Networks with Application in Internet of Vehicles Rui Wang Heju Li Erwu Liu 29 11 0 01 Mar 2021
Machine Unlearning via Algorithmic Stability Enayat Ullah Tung Mai Anup B. Rao Ryan Rossi R. Arora 35 104 0 25 Feb 2021
Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning Da Yu Huishuai Zhang Wei Chen Tie-Yan Liu FedML SILM 94 112 0 25 Feb 2021
Learner-Private Convex Optimization Jiaming Xu Kuang Xu Dana Yang FedML 24 2 0 23 Feb 2021
Obfuscation of Images via Differential Privacy: From Facial Images to General Images W. Croft Jörg-Rüdiger Sack W. Shi PICV 44 22 0 19 Feb 2021
PRICURE: Privacy-Preserving Collaborative Inference in a Multi-Party Setting Ismat Jarin Birhanu Eshete 26 19 0 19 Feb 2021
Domain Impression: A Source Data Free Domain Adaptation Method V. Kurmi Venkatesh Subramanian Vinay P. Namboodiri TTA 151 150 0 17 Feb 2021
Differential Privacy for Government Agencies -- Are We There Yet? Joerg Drechsler 42 20 0 17 Feb 2021
Scaling Neuroscience Research using Federated Learning Dimitris Stripelis J. Ambite Pradeep Lam Paul M. Thompson FedML 53 28 0 16 Feb 2021
Differential Privacy and Byzantine Resilience in SGD: Do They Add Up? R. Guerraoui Nirupam Gupta Rafael Pinot Sébastien Rouault John Stephan 35 30 0 16 Feb 2021
Membership Inference Attacks are Easier on Difficult Problems Avital Shafran Shmuel Peleg Yedid Hoshen MIACV 22 16 0 15 Feb 2021
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation Peter Kairouz Ziyu Liu Thomas Steinke FedML 55 232 0 12 Feb 2021
Private Prediction Sets Anastasios Nikolas Angelopoulos Stephen Bates Tijana Zrnic Michael I. Jordan 26 12 0 11 Feb 2021
Deep Learning with Label Differential Privacy Badih Ghazi Noah Golowich Ravi Kumar Pasin Manurangsi Chiyuan Zhang 54 147 0 11 Feb 2021
Privacy-Preserving Graph Convolutional Networks for Text Classification Timour Igamberdiev Ivan Habernal GNN 33 33 0 10 Feb 2021
CaPC Learning: Confidential and Private Collaborative Learning Christopher A. Choquette-Choo Natalie Dullerud Adam Dziedzic Yunxiang Zhang S. Jha Nicolas Papernot Xiao Wang FedML 73 57 0 09 Feb 2021
Federated Learning with Local Differential Privacy: Trade-offs between Privacy, Utility, and Communication Muah Kim Onur Gunlu Rafael F. Schaefer FedML 110 118 0 09 Feb 2021
Fast and Memory Efficient Differentially Private-SGD via JL Projections Zhiqi Bu Sivakanth Gopi Janardhan Kulkarni Y. Lee J. Shen U. Tantipongpipat FedML 44 41 0 05 Feb 2021
ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models Yugeng Liu Rui Wen Xinlei He A. Salem Zhikun Zhang Michael Backes Emiliano De Cristofaro Mario Fritz Yang Zhang AAML 17 127 0 04 Feb 2021
Federated Intrusion Detection for IoT with Heterogeneous Cohort Privacy Ajesh Koyatan Chathoth Abhyuday N. Jagannatha Stephen Lee 28 14 0 25 Jan 2021
secureTF: A Secure TensorFlow Framework D. Quoc Franz Gregor Sergei Arnautov Roland Kunkel Pramod Bhatotia Christof Fetzer 50 40 0 20 Jan 2021
Exploring Design and Governance Challenges in the Development of Privacy-Preserving Computation Nitin Agrawal Reuben Binns Max Van Kleek Kim Laine N. Shadbolt 26 43 0 20 Jan 2021
Reducing bias and increasing utility by federated generative modeling of medical images using a centralized adversary Jean-Francois Rajotte Soumendu Sundar Mukherjee Caleb Robinson Anthony Ortiz Christopher West J. L. Ferres R. Ng FedML MedIm 133 40 0 18 Jan 2021
Unlearnable Examples: Making Personal Data Unexploitable Hanxun Huang Xingjun Ma S. Erfani James Bailey Yisen Wang MIACV 158 191 0 13 Jan 2021
Robustness of on-device Models: Adversarial Attack to Deep Learning Models on Android Apps Yujin Huang Han Hu Chunyang Chen AAML FedML 87 33 0 12 Jan 2021
Adversary Instantiation: Lower Bounds for Differentially Private Machine Learning Milad Nasr Shuang Song Abhradeep Thakurta Nicolas Papernot Nicholas Carlini MIACV FedML 82 218 0 11 Jan 2021
DiPSeN: Differentially Private Self-normalizing Neural Networks For Adversarial Robustness in Federated Learning Olakunle Ibitoye M. O. Shafiq Ashraf Matrawy FedML 28 18 0 08 Jan 2021