| Extracting training data from large language models N Carlini, F Tramer, E Wallace, M Jagielski, A Herbert-Voss, K Lee, ... 30th USENIX Security Symposium (USENIX Security 21), 2633-2650, 2021 | 1966 | 2021 |
| HAIL: A high-availability and integrity layer for cloud storage KD Bowers, A Juels, A Oprea Proceedings of the 16th ACM conference on Computer and communications …, 2009 | 1462 | 2009 |
| Manipulating machine learning: Poisoning attacks and countermeasures for regression learning M Jagielski, A Oprea, B Biggio, C Liu, C Nita-Rotaru, B Li 2018 IEEE symposium on security and privacy (SP), 19-35, 2018 | 1062 | 2018 |
| Proofs of retrievability: Theory and implementation KD Bowers, A Juels, A Oprea Proceedings of the 2009 ACM workshop on Cloud computing security, 43-54, 2009 | 837 | 2009 |
| Why do adversarial attacks transfer? explaining transferability of evasion and poisoning attacks A Demontis, M Melis, M Pintor, M Jagielski, B Biggio, A Oprea, ... 28th USENIX security symposium (USENIX security 19), 321-338, 2019 | 498 | 2019 |
| Homealone: Co-residency detection in the cloud via side-channel analysis Y Zhang, A Juels, A Oprea, MK Reiter 2011 IEEE symposium on security and privacy, 313-328, 2011 | 494 | 2011 |
| Beehive: Large-scale log analysis for detecting suspicious activity in enterprise networks TF Yen, A Oprea, K Onarlioglu, T Leetham, W Robertson, A Juels, E Kirda Proceedings of the 29th annual computer security applications conference …, 2013 | 420 | 2013 |
| FlipIt: The Game of “Stealthy Takeover” M Van Dijk, A Juels, A Oprea, RL Rivest Journal of Cryptology 26, 655-713, 2013 | 341 | 2013 |
| Detection of malicious web activity in enterprise computer networks AM Oprea, Z Li, R Norris, KD Bowers US Patent 9,838,407, 2017 | 325 | 2017 |
| Auditing differentially private machine learning: How private is Differentially Private SGD? M Jagielski, J Ullman, A Oprea Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS) 2020, 2020 | 256* | 2020 |
| Iris: A scalable cloud file system with efficient integrity checks E Stefanov, M van Dijk, A Juels, A Oprea Proceedings of the 28th Annual Computer Security Applications Conference …, 2012 | 254 | 2012 |
| Detection of early-stage enterprise infection by mining large-scale log data A Oprea, Z Li, TF Yen, SH Chin, S Alrwais 2015 45th Annual IEEE/IFIP International Conference on Dependable Systems …, 2015 | 242 | 2015 |
| Explanation-Guided Backdoor Poisoning Attacks Against Malware Classifiers G Severi, J Meyer, S Coull, A Oprea 30th USENIX Security Symposium (USENIX Security 21), 1487-1504, 2021 | 215 | 2021 |
| New approaches to security and availability for cloud data A Juels, A Oprea Communications of the ACM 56 (2), 64-73, 2013 | 210 | 2013 |
| Differentially private fair learning M Jagielski, M Kearns, J Mao, A Oprea, A Roth, S Sharifi-Malvajerdi, ... International Conference on Machine Learning, 3000-3008, 2019 | 196 | 2019 |
| Scalable cloud file system with efficient integrity checks EP Stefanov, ME Van Dijk, AM Oprea, A Juels US Patent 8,706,701, 2014 | 178 | 2014 |
| Wild patterns reloaded: A survey of machine learning security against training data poisoning AE Cinà, K Grosse, A Demontis, S Vascon, W Zellinger, BA Moser, ... ACM Computing Surveys 55 (13s), 1-39, 2023 | 139 | 2023 |
| How to tell if your cloud files are vulnerable to drive crashes KD Bowers, M Van Dijk, A Juels, A Oprea, RL Rivest Proceedings of the 18th ACM conference on Computer and communications …, 2011 | 134 | 2011 |
| Subpopulation data poisoning attacks M Jagielski, G Severi, N Pousette Harger, A Oprea Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications …, 2021 | 133 | 2021 |
| Anomaly sensor framework for detecting advanced persistent threat attacks TF Yen, A Juels, A Kuppa, K Onarlioglu, A Oprea US Patent 9,378,361, 2016 | 133 | 2016 |
Ari JuelsProfessor, Computer Science, Cornell Tech (Jacobs); Co-Director, IC3確認したメール アドレス: cornell.edu