| Ensemble Adversarial Training: Attacks and Defenses F Tramèr, A Kurakin, N Papernot, I Goodfellow, D Boneh, P McDaniel International Conference on Learning Representations (ICLR), 2018 | 938 | 2018 |
| Stealing machine learning models via prediction apis F Tramèr, F Zhang, A Juels, MK Reiter, T Ristenpart 25th {USENIX} Security Symposium ({USENIX} Security 16), 601-618, 2016 | 596 | 2016 |
| The space of transferable adversarial examples F Tramèr, N Papernot, I Goodfellow, D Boneh, P McDaniel arXiv preprint arXiv:1704.03453, 2017 | 235 | 2017 |
| Advances and open problems in federated learning P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ... arXiv preprint arXiv:1912.04977, 2019 | 178 | 2019 |
| On evaluating adversarial robustness N Carlini, A Athalye, N Papernot, W Brendel, J Rauber, D Tsipras, ... arXiv preprint arXiv:1902.06705, 2019 | 163 | 2019 |
| Physical adversarial examples for object detectors D Song, K Eykholt, I Evtimov, E Fernandes, B Li, A Rahmati, F Tramèr, ... 12th {USENIX} Workshop on Offensive Technologies ({WOOT} 18), 2018 | 113* | 2018 |
| FairTest: Discovering unwarranted associations in data-driven applications F Tramèr, V Atlidakis, R Geambasu, D Hsu, JP Hubaux, M Humbert, ... 2017 IEEE European Symposium on Security and Privacy (EuroS&P), 401-416, 2017 | 76* | 2017 |
| Slalom: Fast, verifiable and private execution of neural networks in trusted hardware F Tramèr, D Boneh International Conference on Learning Representations (ICLR), 2019 | 67 | 2019 |
| Differential privacy with bounded priors: reconciling utility and privacy in genome-wide association studies F Tramèr, Z Huang, JP Hubaux, E Ayday Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications …, 2015 | 66 | 2015 |
| Sealed-glass proofs: Using transparent enclaves to prove and sell knowledge F Tramèr, F Zhang, H Lin, JP Hubaux, A Juels, E Shi 2017 IEEE European Symposium on Security and Privacy (EuroS&P), 19-34, 2017 | 61 | 2017 |
| Formal abstractions for attested execution secure processors R Pass, E Shi, F Tramèr Annual International Conference on the Theory and Applications of …, 2017 | 56 | 2017 |
| Adversarial training and robustness for multiple perturbations F Tramèr, D Boneh Advances in Neural Information Processing Systems, 5866-5876, 2019 | 52 | 2019 |
| Better algorithms for LWE and LWR A Duc, F Tramèr, S Vaudenay Annual International Conference on the Theory and Applications of …, 2015 | 47 | 2015 |
| Privateride: A privacy-enhanced ride-hailing service A Pham, I Dacosta, B Jacot-Guillarmod, K Huguenin, T Hajar, F Tramèr, ... Proceedings on Privacy Enhancing Technologies 2017 (2), 38-56, 2017 | 44 | 2017 |
| Addressing Beacon re-identification attacks: quantification and mitigation of privacy risks JL Raisaro, F Tramèr, Z Ji, D Bu, Y Zhao, K Carey, D Lloyd, H Sofia, ... Journal of the American Medical Informatics Association 24 (4), 799-805, 2017 | 42 | 2017 |
| On adaptive attacks to adversarial example defenses F Tramèr, N Carlini, W Brendel, A Madry arXiv preprint arXiv:2002.08347, 2020 | 38 | 2020 |
| SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems E Chou, F Tramèr, G Pellegrino arXiv, arXiv: 1812.00292, 2018 | 34* | 2018 |
| On solving LPN using BKW and variants S Bogos, F Tramèr, S Vaudenay Cryptography and Communications 8 (3), 331-369, 2016 | 29 | 2016 |
| Enter the hydra: Towards principled bug bounties and exploit-resistant smart contracts L Breidenbach, P Daian, F Tramèr, A Juels 27th {USENIX} Security Symposium ({USENIX} Security 18), 1335-1352, 2018 | 25 | 2018 |
| Fundamental tradeoffs between invariance and sensitivity to adversarial perturbations F Tramèr, J Behrmann, N Carlini, N Papernot, JH Jacobsen arXiv preprint arXiv:2002.04599, 2020 | 18* | 2020 |
Dan BonehProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
