Recent Advances of Differential Privacy in Centralized Deep Learning: A Systematic Survey

28 September 2023

Papers citing "Recent Advances of Differential Privacy in Centralized Deep Learning: A Systematic Survey"

42 / 42 papers shown

Title
A Critical Review on the Use (and Misuse) of Differential Privacy in Machine Learning Alberto Blanco-Justicia David Sánchez J. Domingo-Ferrer K. Muralidhar 57 62 0 09 Jun 2022
Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks Fatemehsadat Mireshghallah Kartik Goyal Archit Uniyal Taylor Berg-Kirkpatrick Reza Shokri MIALM 57 164 0 08 Mar 2022
Debugging Differential Privacy: A Case Study for Privacy Auditing Florian Tramèr Andreas Terzis Thomas Steinke Shuang Song Matthew Jagielski Nicholas Carlini 64 43 0 24 Feb 2022
Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation Chaochao Chen Huiwen Wu Jiajie Su Lingjuan Lyu Xiaolin Zheng L. xilinx Wang 72 74 0 10 Feb 2022
IdentityDP: Differential Private Identification Protection for Face Images Yunqian Wen Li Song Bo Liu Ming Ding Rong Xie PICV 81 65 0 02 Mar 2021
Differentially Private Synthetic Medical Data Generation using Convolutional GANs A. Torfi Edward A. Fox Chandan K. Reddy SyDa MedIm 83 123 0 22 Dec 2020
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown Basel Alomair Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 492 1,923 0 14 Dec 2020
When Machine Learning Meets Privacy: A Survey and Outlook B. Liu Ming Ding Sina shaham W. Rahayu F. Farokhi Zihuai Lin 74 288 0 24 Nov 2020
Synthetic Data -- Anonymisation Groundhog Day Theresa Stadler Bristena Oprisanu Carmela Troncoso 75 159 0 13 Nov 2020
Survey on Causal-based Machine Learning Fairness Notions K. Makhlouf Sami Zhioua C. Palamidessi FaML 54 85 0 19 Oct 2020
Neither Private Nor Fair: Impact of Data Imbalance on Utility and Fairness in Differential Privacy Tom Farrand Fatemehsadat Mireshghallah Sahib Singh Andrew Trask FedML 47 93 0 10 Sep 2020
More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence Tianqing Zhu Dayong Ye Wei Wang Wanlei Zhou Philip S. Yu SyDa 66 128 0 05 Aug 2020
Tempered Sigmoid Activations for Deep Learning with Differential Privacy Nicolas Papernot Abhradeep Thakurta Shuang Song Steve Chien Ulfar Erlingsson AAML 187 179 0 28 Jul 2020
A Survey of Privacy Attacks in Machine Learning M. Rigaki Sebastian Garcia PILM AAML 79 222 0 15 Jul 2020
Towards Differentially Private Text Representations Lingjuan Lyu Yitong Li Xuanli He Tong Xiao 58 39 0 25 Jun 2020
GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators Dingfan Chen Tribhuvanesh Orekondy Mario Fritz SyDa 56 185 0 15 Jun 2020
Auditing Differentially Private Machine Learning: How Private is Private SGD? Matthew Jagielski Jonathan R. Ullman Alina Oprea FedML 74 245 0 13 Jun 2020
Privacy Preserving Face Recognition Utilizing Differential Privacy Pathum Chamikara Mahawaga Arachchige P. Bertók I. Khalil D. Liu S. Çamtepe PICV 69 119 0 21 May 2020
Privacy in Deep Learning: A Survey Fatemehsadat Mirshghallah Mohammadkazem Taram Praneeth Vepakomma Abhishek Singh Ramesh Raskar H. Esmaeilzadeh FedML 75 138 0 25 Apr 2020
Causal Interpretability for Machine Learning -- Problems, Methods and Evaluation Raha Moraffah Mansooreh Karami Ruocheng Guo A. Raglin Huan Liu CML ELM XAI 65 219 0 09 Mar 2020
Guidelines for Implementing and Auditing Differentially Private Systems Daniel Kifer Solomon Messing Aaron Roth Abhradeep Thakurta Qiang Yan 40 34 0 10 Feb 2020
An Adaptive and Fast Convergent Approach to Differentially Private Deep Learning Zhiying Xu Shuyu Shi A. Liu Jun Zhao Lin Chen FedML 80 37 0 19 Dec 2019
Linear Mode Connectivity and the Lottery Ticket Hypothesis Jonathan Frankle Gintare Karolina Dziugaite Daniel M. Roy Michael Carbin MoMe 156 619 0 11 Dec 2019
The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks Yuheng Zhang R. Jia Hengzhi Pei Wenxiao Wang Yue Liu Basel Alomair AAML 113 419 0 17 Nov 2019
Robust Anomaly Detection and Backdoor Attack Detection Via Differential Privacy Min Du R. Jia Basel Alomair AAML 72 176 0 16 Nov 2019
Leveraging Hierarchical Representations for Preserving Privacy and Utility in Text Oluwaseyi Feyisetan Tom Diethe Thomas Drake 67 74 0 20 Oct 2019
SoK: Differential Privacies Damien Desfontaines Balázs Pejó 66 124 0 04 Jun 2019
P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification Bingzhe Wu Shiwan Zhao Guangyu Sun Xiaolu Zhang Zhong Su C. Zeng Zhihong Liu 60 41 0 30 May 2019
Differential Privacy Has Disparate Impact on Model Accuracy Eugene Bagdasaryan Vitaly Shmatikov 149 481 0 28 May 2019
Why gradient clipping accelerates training: A theoretical justification for adaptivity J.N. Zhang Tianxing He S. Sra Ali Jadbabaie 76 464 0 28 May 2019
Differentially Private Model Publishing for Deep Learning Lei Yu Ling Liu C. Pu Mehmet Emre Gursoy Stacey Truex FedML 71 265 0 03 Apr 2019
Generalised Differential Privacy for Text Document Processing Natasha Fernandes Mark Dras Annabelle McIver 41 107 0 26 Nov 2018
Adversarial Robustness Toolbox v1.0.0 Maria-Irina Nicolae M. Sinn Minh-Ngoc Tran Beat Buesser Ambrish Rawat ... Nathalie Baracaldo Bryant Chen Heiko Ludwig Ian Molloy Ben Edwards AAML VLM 77 458 0 03 Jul 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Jonathan Frankle Michael Carbin 240 3,473 0 09 Mar 2018
Differentially Private Generative Adversarial Network Liyang Xie Kaixiang Lin Shu Wang Fei Wang Jiayu Zhou SyDa 90 500 0 19 Feb 2018
Certified Robustness to Adversarial Examples with Differential Privacy Mathias Lécuyer Vaggelis Atlidakis Roxana Geambasu Daniel J. Hsu Suman Jana SILM AAML 96 934 0 09 Feb 2018
Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning Xinyun Chen Chang-rui Liu Yue Liu Kimberly Lu Basel Alomair AAML SILM 143 1,840 0 15 Dec 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 283 8,904 0 25 Aug 2017
Improved Training of Wasserstein GANs Ishaan Gulrajani Faruk Ahmed Martín Arjovsky Vincent Dumoulin Aaron Courville GAN 207 9,548 0 31 Mar 2017
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 261 4,135 0 18 Oct 2016
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 216 6,130 0 01 Jul 2016
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 277 19,066 0 20 Dec 2014