| Website fingerprinting defenses at the application layer G Cherubin, J Hayes, M Juarez Proceedings on Privacy Enhancing Technologies 2017 (2), 186-203, 2017 | 92 | 2017 |
| Reconstructing training data with informed adversaries B Balle, G Cherubin, J Hayes 2022 IEEE Symposium on Security and Privacy (SP), 1138-1156, 2022 | 66 | 2022 |
| Synthetic Data--what, why and how? J Jordon, L Szpruch, F Houssiau, M Bottarelli, G Cherubin, C Maple, ... arXiv preprint arXiv:2205.03257, 2022 | 62 | 2022 |
| Bayes, not Naïve: Security Bounds on Website Fingerprinting Defenses G Cherubin Proceedings on Privacy Enhancing Technologies 2017 (4), 215-231, 2017 | 45 | 2017 |
| Disparate vulnerability: On the unfairness of privacy attacks against machine learning M Yaghini, B Kulynych, G Cherubin, C Troncoso arXiv e-prints, arXiv: 1906.00389, 2019 | 40 | 2019 |
| Online website fingerprinting: Evaluating website fingerprinting attacks on Tor in the real world G Cherubin, R Jansen, C Troncoso 31st USENIX Security Symposium (USENIX Security 22), 753-770, 2022 | 33 | 2022 |
| F-BLEAU: fast black-box leakage estimation G Cherubin, K Chatzikokolakis, C Palamidessi 2019 IEEE Symposium on Security and Privacy (SP), 835-852, 2019 | 33 | 2019 |
| Disparate vulnerability to membership inference attacks B Kulynych, M Yaghini, G Cherubin, M Veale, C Troncoso arXiv preprint arXiv:1906.00389, 2019 | 27 | 2019 |
| Conformal clustering and its application to botnet traffic G Cherubin, I Nouretdinov, A Gammerman, R Jordaney, Z Wang, D Papini, ... Statistical Learning and Data Sciences: Third International Symposium, SLDS …, 2015 | 22 | 2015 |
| Majority Vote Ensembles of Conformal Predictors G Cherubin | 17 | 2018 |
| Exact Optimization of Conformal Predictors via Incremental and Decremental Learning G Cherubin, K Chatzikokolakis, M Jaggi Proceedings of the 38th International Conference on Machine Learning 139 …, 2021 | 13 | 2021 |
| SoK: Let the privacy games begin! A unified treatment of data inference privacy in machine learning A Salem, G Cherubin, D Evans, B Köpf, A Paverd, A Suri, S Tople, ... 2023 IEEE Symposium on Security and Privacy (SP), 327-345, 2023 | 6 | 2023 |
| Approximating full conformal prediction at scale via influence functions J Abad, U Bhatt, A Weller, G Cherubin arXiv preprint arXiv:2202.01315, 2022 | 5 | 2022 |
| The Bayes security measure K Chatzikokolakis, G Cherubin, C Palamidessi, C Troncoso arXiv preprint arXiv:2011.03396, 2020 | 5 | 2020 |
| Exchangeability martingales for selecting features in anomaly detection G Cherubin, A Baldwin, J Griffin Conformal and Probabilistic Prediction and Applications, 157-170, 2018 | 5 | 2018 |
| Synthetic data–what, why and how?, 2022 J Jordon, L Szpruch, F Houssiau, M Bottarelli, G Cherubin, C Maple, ... URL https://arxiv. org/abs/2205.03257, 0 | 5 | |
| Hidden markov models with confidence G Cherubin, I Nouretdinov Symposium on Conformal and Probabilistic Prediction with Applications, 128-144, 2016 | 3 | 2016 |
| Bots detection by Conformal Clustering G Cherubin MSc thesis, Royal Holloway, 2014. URL https://giocher. com/files/docs/bdcc …, 2014 | 3 | 2014 |
| Bayes Security: A Not So Average Metric K Chatzikokolakis, G Cherubin, C Palamidessi, C Troncoso 2023 IEEE 36th Computer Security Foundations Symposium (CSF), 388-406, 2023 | 2 | 2023 |
| Fast conformal classification using influence functions U Bhatt, A Weller, G Cherubin Conformal and Probabilistic Prediction and Applications, 303-305, 2021 | 1 | 2021 |
Jamie HayesGoogle DeepMindVerified email at google.com
