| 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 | 7126 | 2017 |
| Exploiting Unintended Feature Leakage in Collaborative Learning L Melis, C Song, E De Cristofaro, V Shmatikov IEEE Symposium on Security and Privacy (S&P), Oakland, 2019 | 2459 | 2019 |
| Machine Learning Models that Remember Too Much C Song, T Ristenpart, V Shmatikov The ACM Conference on Computer and Communications Security, 2017 | 789 | 2017 |
| Information leakage in embedding models C Song, A Raghunathan The ACM SIGSAC Conference on Computer and Communications Security, 377-390, 2020 | 392 | 2020 |
| Auditing Data Provenance in Text-Generation Models C Song, V Shmatikov The ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019 | 361 | 2019 |
| Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models S Yousefi, F Amrollahi, M Amgad, C Dong, JE Lewis, C Song, DA Gutman, ... Scientific Reports 7, 2017 | 283 | 2017 |
| Chiron: Privacy-preserving Machine Learning as a Service T Hunt, C Song, R Shokri, V Shmatikov, E Witchel arXiv preprint arXiv:1803.05961, 2018 | 281 | 2018 |
| You Autocomplete Me: Poisoning Vulnerabilities in Neural Code Completion R Schuster, C Song, E Tromer, V Shmatikov The 30th USENIX Security symposium, 2021 | 246 | 2021 |
| Overlearning Reveals Sensitive Attributes C Song, V Shmatikov International Conference on Learning Representations, 2020 | 213 | 2020 |
| Generalized Zero-Shot Text Classification for ICD Coding C Song, S Zhang, N Sadoughi, P Xie, E Xing International Joint Conference on Artificial Intelligence (IJCAI), 2020 | 83* | 2020 |
| Adversarial Semantic Collisions C Song, AM Rush, V Shmatikov Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020 | 67 | 2020 |
| Fooling OCR Systems with Adversarial Text Images C Song, V Shmatikov arXiv preprint arXiv:1802.05385, 2018 | 63 | 2018 |
| FLAIR: Federated Learning Annotated Image Repository C Song, F Granqvist, K Talwar Advances in Neural Information Processing Systems 35, 37792-37805, 2022 | 42 | 2022 |
| Training Large-Vocabulary Neural Language Models by Private Federated Learning for Resource-Constrained Devices M Xu, C Song, Y Tian, N Agrawal, F Granqvist, R van Dalen, X Zhang, ... ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 31 | 2023 |
| Samplable anonymous aggregation for private federated data analysis K Talwar, S Wang, A McMillan, V Feldman, P Bansal, B Basile, A Cahill, ... Proceedings of the 2024 on ACM SIGSAC Conference on Computer and …, 2024 | 24 | 2024 |
| Cell-phone traces reveal infection-associated behavioral change Y Vigfusson, TA Karlsson, D Onken, C Song, AF Einarsson, N Kishore, ... Proceedings of the National Academy of Sciences 118 (6), e2005241118, 2021 | 20 | 2021 |
| Learning Genomic Representations to Predict Clinical Outcomes in Cancer S Yousefi, C Song, N Nauata, L Cooper arXiv preprint arXiv:1609.08663, 2016 | 17 | 2016 |
| Membership Encoding for Deep Learning C Song, R Shokri The ACM ASIA Conference on Computer and Communications Security, 2020 | 16 | 2020 |
| Private Federated Statistics in an Interactive Setting A McMillan, O Javidbakht, K Talwar, E Briggs, M Chatzidakis, J Chen, ... arXiv preprint arXiv:2211.10082, 2022 | 10 | 2022 |
| Private Federated Learning In Real World Application--A Case Study A Ji, B Bandyopadhyay, C Song, N Krishnaswami, P Vashisht, R Smiroldo, ... arXiv preprint arXiv:2502.04565, 2025 | 8 | 2025 |
Vitaly ShmatikovCornell TechVerified email at cs.cornell.edu
