Title
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 307 1,059 0 29 Nov 2018
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 203 430 0 29 Nov 2018
Distributed Differential Privacy via Shuffling Albert Cheu Adam D. Smith Jonathan R. Ullman David Zeber M. Zhilyaev FedML 99 352 0 04 Aug 2018
Subsampled Rényi Differential Privacy and Analytical Moments Accountant Yu Wang Borja Balle S. Kasiviswanathan 88 401 0 31 Jul 2018
How To Backdoor Federated Learning Eugene Bagdasaryan Andreas Veit Yiqing Hua D. Estrin Vitaly Shmatikov SILM FedML 104 1,929 0 02 Jul 2018
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware Florian Tramèr Dan Boneh FedML 184 401 0 08 Jun 2018
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising Borja Balle Yu Wang MLT 97 413 0 16 May 2018
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 159 1,482 0 10 May 2018
The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks Nicholas Carlini Chang-rui Liu Ulfar Erlingsson Jernej Kos Basel Alomair 155 1,149 0 22 Feb 2018
signSGD: Compressed Optimisation for Non-Convex Problems Jeremy Bernstein Yu Wang Kamyar Azizzadenesheli Anima Anandkumar FedML ODL 103 1,051 0 13 Feb 2018
Collecting Telemetry Data Privately Bolin Ding Janardhan Kulkarni Sergey Yekhanin 62 689 0 05 Dec 2017
Prochlo: Strong Privacy for Analytics in the Crowd Andrea Bittau Ulfar Erlingsson Petros Maniatis Ilya Mironov A. Raghunathan David Lie Mitch Rudominer Ushasree Kode J. Tinnés B. Seefeld 151 279 0 02 Oct 2017
Prio: Private, Robust, and Scalable Computation of Aggregate Statistics Henry Corrigan-Gibbs Dan Boneh 44 354 0 18 Mar 2017
Renyi Differential Privacy Ilya Mironov 91 1,268 0 24 Feb 2017
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 280 4,160 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 6,172 0 01 Jul 2016
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds Mark Bun Thomas Steinke 97 840 0 06 May 2016
Learning with Differential Privacy: Stability, Learnability and the Sufficiency and Necessity of ERM Principle Yu Wang Jing Lei S. Fienberg 95 103 0 23 Feb 2015
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response Ulfar Erlingsson Vasyl Pihur Aleksandra Korolova 109 2,001 0 25 Jul 2014
Differentially Private Empirical Risk Minimization Kamalika Chaudhuri C. Monteleoni Anand D. Sarwate 164 1,490 0 01 Dec 2009
What Can We Learn Privately? S. Kasiviswanathan Homin K. Lee Kobbi Nissim Sofya Raskhodnikova Adam D. Smith 137 1,474 0 06 Mar 2008