| Membership Inference Attacks against Machine Learning Models R Shokri, M Stronati, C Song, V Shmatikov IEEE Symposium on Security and Privacy (S&P), Oakland, 2017 | 5370 | 2017 |
| Privacy-Preserving Deep Learning R Shokri, V Shmatikov ACM Conference on Computer and Communications Security (CCS), 2015 | 2951 | 2015 |
| Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning M Nasr, R Shokri, A Houmansadr IEEE Symposium on Security and Privacy (S&P), Oakland, 2019 | 2035* | 2019 |
| Quantifying Location Privacy R Shokri, G Theodorakopoulos, JY Le Boudec, JP Hubaux IEEE Symposium on Security and Privacy (S&P), Oakland, 2011 | 960 | 2011 |
| Machine Learning with Membership Privacy using Adversarial Regularization M Nasr, R Shokri, A Houmansadr ACM Conference on Computer and Communications Security (CCS), 2018 | 553 | 2018 |
| Protecting Location Privacy: Optimal Strategy Against Localization Attacks R Shokri, G Theodorakopoulos, C Troncoso, JP Hubaux, JY Le Boudec ACM conference on Computer and Communications Security (CCS), 2012 | 533 | 2012 |
| Privacy Risks of Securing Machine Learning Models against Adversarial Examples L Song, R Shokri, P Mittal ACM Conference on Computer and Communications Security (CCS), 2019 | 395* | 2019 |
| Synthesizing Plausible Privacy-Preserving Location Traces V Bindschaedler, R Shokri IEEE Symposium on Security and Privacy (S&P), Oakland, 2016 | 269 | 2016 |
| Enhanced Membership Inference Attacks against Machine Learning Models J Ye, A Maddi, SK Murakonda, V Bindschaedler, R Shokri ACM Conference on Computer and Communications Security (CCS), 2022 | 258 | 2022 |
| Chiron: Privacy-Preserving Machine Learning as a Service T Hunt, C Song, R Shokri, V Shmatikov, E Witchel arXiv preprint arXiv:1803.05961, 2018 | 251 | 2018 |
| What Does it Mean for a Language Model to Preserve Privacy? H Brown, K Lee, F Mireshghallah, R Shokri, F Tramèr ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2022 | 244 | 2022 |
| On the Optimal Placement of Mix Zones J Freudiger, R Shokri, JP Hubaux Privacy Enhancing Technologies Symposium (PETS), 2009 | 244 | 2009 |
| Hiding in the Mobile Crowd: Location Privacy through Collaboration R Shokri, G Theodorakopoulos, P Papadimitratos, E Kazemi, JP Hubaux IEEE Transactions on Dependable and Secure Computing (TDSC), 2014 | 234 | 2014 |
| Defeating Image Obfuscation with Deep Learning R McPherson, R Shokri, V Shmatikov arXiv preprint arXiv:1609.00408, 2016 | 214 | 2016 |
| Evaluating the Privacy Risk of Location-based Services J Freudiger, R Shokri, JP Hubaux Financial Cryptography and Data Security, 2012 | 208 | 2012 |
| Plausible Deniability for Privacy-Preserving Data Synthesis V Bindschaedler, R Shokri, C Gunter VLDB Endowment International Conference on Very Large Data Bases (PVLDB), 2017 | 205 | 2017 |
| Cronus: Robust and heterogeneous collaborative learning with black-box knowledge transfer H Chang, V Shejwalkar, R Shokri, A Houmansadr arXiv preprint arXiv:1912.11279, 2019 | 198 | 2019 |
| Privacy Games: Optimal User-Centric Data Obfuscation R Shokri Privacy Enhancing Technologies Symposium (PETS), 2015 | 191 | 2015 |
| Unraveling an Old Cloak: K-anonymity for Location Privacy R Shokri, C Troncoso, C Diaz, J Freudiger, JP Hubaux ACM workshop on Privacy in the electronic society (WPES), 2010 | 191 | 2010 |
| On the Privacy Risks of Model Explanations R Shokri, M Strobel, Y Zick AAAI/ACM Conference on AI, Ethics, and Society (AIES), 2021 | 182* | 2021 |
Jean-Pierre HubauxProfessor, EPFL確認したメール アドレス: epfl.ch