Deep Learning with Differential Privacy

1 July 2016

Papers citing "Deep Learning with Differential Privacy"

50 / 1,146 papers shown

Title
CryptoTL: Private, Efficient and Secure Transfer Learning Roman Walch Samuel Sousa Lukas Helminger Stefanie N. Lindstaedt Christian Rechberger A. Trugler 38 8 0 24 May 2022
PrivFairFL: Privacy-Preserving Group Fairness in Federated Learning Sikha Pentyala Nicola Neophytou A. Nascimento Martine De Cock G. Farnadi 47 17 0 23 May 2022
LIA: Privacy-Preserving Data Quality Evaluation in Federated Learning Using a Lazy Influence Approximation Ljubomir Rokvic Panayiotis Danassis Sai Praneeth Karimireddy Boi Faltings TDI 37 1 0 23 May 2022
Time-series Transformer Generative Adversarial Networks Padmanaba Srinivasan William J. Knottenbelt AI4TS 28 13 0 23 May 2022
FaceMAE: Privacy-Preserving Face Recognition via Masked Autoencoders Kaidi Wang Bo Zhao Xiangyu Peng Zheng Hua Zhu Jiankang Deng Xinchao Wang Hakan Bilen Yang You PICV 60 11 0 23 May 2022
Differential Privacy: What is all the noise about? Roxana Dánger Mercaderes 43 3 0 19 May 2022
Recovering Private Text in Federated Learning of Language Models Samyak Gupta Yangsibo Huang Zexuan Zhong Tianyu Gao Kai Li Danqi Chen FedML 40 75 0 17 May 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Yangqiu Song Jian Pei 47 104 0 16 May 2022
On the Importance of Architecture and Feature Selection in Differentially Private Machine Learning Wenxuan Bao L. A. Bauer Vincent Bindschaedler OOD 34 4 0 13 May 2022
Secure Aggregation for Federated Learning in Flower Kwing Hei Li Pedro Porto Buarque de Gusmão Daniel J. Beutel Nicholas D. Lane FedML 37 36 0 12 May 2022
Blockchain-based Secure Client Selection in Federated Learning Truc D. T. Nguyen Phuc Thai Tre' R. Jeter Thang N. Dinh My T. Thai 33 12 0 11 May 2022
Privacy Enhancement for Cloud-Based Few-Shot Learning Archit Parnami Muhammad Usama Liyue Fan Minwoo Lee 27 1 0 10 May 2022
Decentralized Stochastic Optimization with Inherent Privacy Protection Yongqiang Wang H. Vincent Poor 31 37 0 08 May 2022
$Privacy accounting $\varepsilon$conomics: Improving differential privacy composition via a posteriori bounds$ Privacy accounting $\varepsilon$ conomics: Improving differential privacy composition via a posteriori bounds Valentin Hartmann Vincent Bindschaedler Alexander Bentkamp Robert West 29 1 0 06 May 2022
Synthetic Data -- what, why and how? James Jordon Lukasz Szpruch F. Houssiau M. Bottarelli Giovanni Cherubin Carsten Maple Samuel N. Cohen Adrian Weller 51 109 0 06 May 2022
Generative Adversarial Network Based Synthetic Learning and a Novel Domain Relevant Loss Term for Spine Radiographs E. Schonfeld A. Veeravagu MedIm 26 1 0 05 May 2022
Provably Confidential Language Modelling Xuandong Zhao Lei Li Yu Wang MU 39 15 0 04 May 2022
Symbolic analysis meets federated learning to enhance malware identifier Khanh-Huu-The Dam Charles-Henry Bertrand Van Ouytsel Axel Legay FedML 34 5 0 29 Apr 2022
Sharper Utility Bounds for Differentially Private Models Yilin Kang Yong Liu Jian Li Weiping Wang FedML 37 3 0 22 Apr 2022
Special Session: Towards an Agile Design Methodology for Efficient, Reliable, and Secure ML Systems Shail Dave Alberto Marchisio Muhammad Abdullah Hanif Amira Guesmi Aviral Shrivastava Ihsen Alouani Mohamed Bennai 39 13 0 18 Apr 2022
A Differentially Private Probabilistic Framework for Modeling the Variability Across Federated Datasets of Heterogeneous Multi-View Observations Irene Balelli Santiago Silva Marco Lorenzi FedML 42 5 0 15 Apr 2022
Federated Learning with Partial Model Personalization Krishna Pillutla Kshitiz Malik Abdel-rahman Mohamed Michael G. Rabbat Maziar Sanjabi Lin Xiao FedML 43 157 0 08 Apr 2022
Adversarial Analysis of the Differentially-Private Federated Learning in Cyber-Physical Critical Infrastructures Md Tamjid Hossain S. Badsha Hung M. La Haoting Shen Shafkat Islam Ibrahim Khalil X. Yi AAML 32 3 0 06 Apr 2022
User-Level Differential Privacy against Attribute Inference Attack of Speech Emotion Recognition in Federated Learning Tiantian Feng Raghuveer Peri Shrikanth Narayanan FedML 20 28 0 05 Apr 2022
ScaleSFL: A Sharding Solution for Blockchain-Based Federated Learning Evan W. R. Madill Ben Nguyen C. Leung Sara Rouhani 43 20 0 04 Apr 2022
A Differentially Private Framework for Deep Learning with Convexified Loss Functions Zhigang Lu Hassan Jameel Asghar M. Kâafar Darren Webb Peter Dickinson 80 15 0 03 Apr 2022
CTAB-GAN+: Enhancing Tabular Data Synthesis Zilong Zhao A. Kunar Robert Birke L. Chen 38 78 0 01 Apr 2022
Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets Florian Tramèr Reza Shokri Ayrton San Joaquin Hoang Minh Le Matthew Jagielski Sanghyun Hong Nicholas Carlini MIACV 56 109 0 31 Mar 2022
Distributed data analytics Richard Mortier Hamed Haddadi S. S. Rodríguez Liang Wang 29 2 0 26 Mar 2022
Knowledge Removal in Sampling-based Bayesian Inference Shaopeng Fu Fengxiang He Dacheng Tao BDL MU 30 27 0 24 Mar 2022
Adaptive Aggregation For Federated Learning K.R. Jayaram Vinod Muthusamy Gegi Thomas Ashish Verma Mark Purcell FedML 38 16 0 23 Mar 2022
Training a Tokenizer for Free with Private Federated Learning Eugene Bagdasaryan Congzheng Song Rogier van Dalen M. Seigel Áine Cahill FedML 27 5 0 15 Mar 2022
A review of Generative Adversarial Networks for Electronic Health Records: applications, evaluation measures and data sources Ghadeer O. Ghosheh Jin Li T. Zhu 37 32 0 14 Mar 2022
One Parameter Defense -- Defending against Data Inference Attacks via Differential Privacy Dayong Ye Sheng Shen Tianqing Zhu B. Liu Wanlei Zhou MIACV 16 62 0 13 Mar 2022
No Free Lunch Theorem for Security and Utility in Federated Learning Xiaojin Zhang Hanlin Gu Lixin Fan Kai Chen Qiang Yang FedML 26 64 0 11 Mar 2022
Differentially Private Learning Needs Hidden State (Or Much Faster Convergence) Jiayuan Ye Reza Shokri FedML 37 44 0 10 Mar 2022
Similarity-based Label Inference Attack against Training and Inference of Split Learning Junlin Liu Xinchen Lyu Qimei Cui Xiaofeng Tao FedML 37 26 0 10 Mar 2022
Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks Fatemehsadat Mireshghallah Kartik Goyal Archit Uniyal Taylor Berg-Kirkpatrick Reza Shokri MIALM 32 152 0 08 Mar 2022
Differential Privacy Amplification in Quantum and Quantum-inspired Algorithms Armando Angrisani Mina Doosti E. Kashefi 26 12 0 07 Mar 2022
Acceleration of Federated Learning with Alleviated Forgetting in Local Training Chencheng Xu Zhiwei Hong Minlie Huang Tao Jiang FedML 34 46 0 05 Mar 2022
Differentially Private Label Protection in Split Learning Xin Yang Jiankai Sun Yuanshun Yao Junyuan Xie Chong-Jun Wang FedML 52 36 0 04 Mar 2022
Label-Only Model Inversion Attacks via Boundary Repulsion Mostafa Kahla Si-An Chen H. Just R. Jia 35 74 0 03 Mar 2022
Label Leakage and Protection from Forward Embedding in Vertical Federated Learning Jiankai Sun Xin Yang Yuanshun Yao Chong-Jun Wang FedML 41 37 0 02 Mar 2022
Faking feature importance: A cautionary tale on the use of differentially-private synthetic data Oscar Giles Kasra Hosseini Grigorios Mingas Oliver Strickson Louise A. Bowler ... A. Heppenstall N. Lomax N. Malleson Martin O'Reilly Sebastian Vollmerteke 29 8 0 02 Mar 2022
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation Sina Sajadmanesh Ali Shahin Shamsabadi A. Bellet D. Gática-Pérez 40 63 0 02 Mar 2022
MIAShield: Defending Membership Inference Attacks via Preemptive Exclusion of Members Ismat Jarin Birhanu Eshete 47 9 0 02 Mar 2022
Bounding Membership Inference Anvith Thudi Ilia Shumailov Franziska Boenisch Nicolas Papernot 38 18 0 24 Feb 2022
Debugging Differential Privacy: A Case Study for Privacy Auditing Florian Tramèr Andreas Terzis Thomas Steinke Shuang Song Matthew Jagielski Nicholas Carlini 25 42 0 24 Feb 2022
Exploring the Unfairness of DP-SGD Across Settings Frederik Noe R. Herskind Anders Søgaard 27 4 0 24 Feb 2022
Differentially Private Estimation of Heterogeneous Causal Effects Fengshi Niu Harsha Nori B. Quistorff R. Caruana Donald Ngwe A. Kannan CML 30 13 0 22 Feb 2022