| Membership inference attacks against machine learning models R Shokri, M Stronati, C Song, V Shmatikov 2017 IEEE symposium on security and privacy (SP), 3-18, 2017 | 4559 | 2017 |
| Robust de-anonymization of large sparse datasets A Narayanan, V Shmatikov 2008 IEEE Symposium on Security and Privacy (sp 2008), 111-125, 2008 | 3369 | 2008 |
| Privacy-preserving deep learning R Shokri, V Shmatikov Proceedings of the 22nd ACM SIGSAC conference on computer and communications …, 2015 | 2684 | 2015 |
| How to backdoor federated learning E Bagdasaryan, A Veit, Y Hua, D Estrin, V Shmatikov International conference on artificial intelligence and statistics, 2938-2948, 2020 | 2010 | 2020 |
| De-anonymizing social networks A Narayanan, V Shmatikov 2009 30th IEEE symposium on security and privacy, 173-187, 2009 | 1810 | 2009 |
| Exploiting unintended feature leakage in collaborative learning L Melis, C Song, E De Cristofaro, V Shmatikov 2019 IEEE symposium on security and privacy (SP), 691-706, 2019 | 1672 | 2019 |
| Airavat: Security and privacy for MapReduce. I Roy, STV Setty, A Kilzer, V Shmatikov, E Witchel NSDI 10, 297-312, 2010 | 703 | 2010 |
| The most dangerous code in the world: validating SSL certificates in non-browser software M Georgiev, S Iyengar, S Jana, R Anubhai, D Boneh, V Shmatikov Proceedings of the 2012 ACM conference on Computer and communications …, 2012 | 681 | 2012 |
| Fast dictionary attacks on passwords using time-space tradeoff A Narayanan, V Shmatikov Proceedings of the 12th ACM conference on Computer and communications …, 2005 | 601 | 2005 |
| Machine learning models that remember too much C Song, T Ristenpart, V Shmatikov Proceedings of the 2017 ACM SIGSAC Conference on computer and communications …, 2017 | 598 | 2017 |
| How to break anonymity of the netflix prize dataset A Narayanan, V Shmatikov arXiv preprint cs/0610105, 2006 | 533 | 2006 |
| Myths and fallacies of" personally identifiable information" A Narayanan, V Shmatikov Communications of the ACM 53 (6), 24-26, 2010 | 516 | 2010 |
| Differential privacy has disparate impact on model accuracy E Bagdasaryan, O Poursaeed, V Shmatikov Advances in neural information processing systems 32, 2019 | 507 | 2019 |
| The cost of privacy: destruction of data-mining utility in anonymized data publishing J Brickell, V Shmatikov Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008 | 498 | 2008 |
| Constraint solving for bounded-process cryptographic protocol analysis J Millen, V Shmatikov Proceedings of the 8th ACM conference on Computer and Communications …, 2001 | 484 | 2001 |
| " You might also like:" Privacy risks of collaborative filtering JA Calandrino, A Kilzer, A Narayanan, EW Felten, V Shmatikov 2011 IEEE symposium on security and privacy, 231-246, 2011 | 424 | 2011 |
| Timing analysis in low-latency mix networks: Attacks and defenses V Shmatikov, MH Wang Computer Security–ESORICS 2006: 11th European Symposium on Research in …, 2006 | 360 | 2006 |
| Blind backdoors in deep learning models E Bagdasaryan, V Shmatikov 30th USENIX Security Symposium (USENIX Security 21), 1505-1521, 2021 | 297 | 2021 |
| Salvaging federated learning by local adaptation T Yu, E Bagdasaryan, V Shmatikov arXiv preprint arXiv:2002.04758, 2020 | 281 | 2020 |
| Finite-State Analysis of SSL 3.0. JC Mitchell, V Shmatikov, U Stern USENIX Security Symposium 1, 201-216, 1998 | 275 | 1998 |
