| Rofl: Robustness of secure federated learning H Lycklama, L Burkhalter, A Viand, N Küchler, A Hithnawi 2023 IEEE Symposium on Security and Privacy (SP), 453-476, 2023 | 118* | 2023 |
| Zeph: Cryptographic Enforcement of End-to-End Data Privacy L Burkhalter, N Küchler, A Viand, H Shafagh, A Hithnawi 15th {USENIX} Symposium on Operating Systems Design and Implementation …, 2021 | 38 | 2021 |
| Cohere: Managing Differential Privacy in Large Scale Systems N Küchler, E Opel, H Lycklama, A Viand, A Hithnawi 2024 IEEE Symposium on Security and Privacy (SP), 2023 | 11* | 2023 |
| Holding Secrets Accountable: Auditing Privacy-Preserving Machine Learning H Lycklama, A Viand, N Küchler, C Knabenhans, A Hithnawi arXiv preprint arXiv:2402.15780, 2024 | 5 | 2024 |
| Cryptographic Auditing for Collaborative Learning H Lycklama, N Küchler, A Viand, E Opel, L Burkhalter, A Hithnawi NeurIPS ML Safety Workshop, 2022 | 3 | 2022 |
| Artemis: Efficient Commit-and-Prove SNARKs for zkML H Lycklama, A Viand, N Avramov, N Küchler, A Hithnawi arXiv preprint arXiv:2409.12055, 2024 | 1 | 2024 |
Anwar HithnawiUniversity of TorontoVerified email at cs.toronto.edu