| A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics SA Osia, AS Shamsabadi, A Taheri, HR Rabiee, N Lane, H Haddadi IEEE Internet of Things Journal, 2020 | 304 | 2020 |
| QUOTIENT: Two-Party Secure Neural Network Training and Prediction N Agrawal, AS Shamsabadi, MJ Kusner, A Gascón 26th ACM Conference on Computer and Communications Security (CCS), 2019, 2019 | 261 | 2019 |
| When the curious abandon honesty: Federated learning is not private F Boenisch, A Dziedzic, R Schuster, AS Shamsabadi, I Shumailov, ... 2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P), 175-199, 2023 | 211 | 2023 |
| DarkneTZ: Towards Model Privacy at the Edge using Trusted Execution Environments F Mo, AS Shamsabadi, K Katevas, S Demetriou, I Leontiadis, A Cavallaro, ... ACM International Conference on Mobile Systems, Applications, and Services …, 2020 | 211 | 2020 |
| ColorFool: Semantic Adversarial Colorization AS Shamsabadi, R Sanchez-Matilla, A Cavallaro Conference on Computer Vision and Pattern Recognition (CVPR), 2020 | 146 | 2020 |
| Deep Private-Feature Extraction SA Osia, A Taheri, AS Shamsabadi, K Katevas, H Haddadi, HR Rabiee IEEE Transactions on Knowledge and Data Engineering, 2018 | 127 | 2018 |
| GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation S Sajadmanesh, AS Shamsabadi, A Bellet, D Gatica-Perez 32nd USENIX Security Symposium, 2022 | 76 | 2022 |
| Private and scalable personal data analytics using hybrid edge-to-cloud deep learning SA Osia, AS Shamsabadi, A Taheri, HR Rabiee, H Haddadi Computer 51 (5), 42-49, 2018 | 56 | 2018 |
| FoolHD: Fooling speaker identification by Highly imperceptible adversarial Disturbances AS Shamsabadi, FS Teixeira, A Abad, B Raj, A Cavallaro, I Trancoso 46th IEEE International Conference on Acoustics, Speech, and Signal …, 2021 | 38 | 2021 |
| Differentially private speaker anonymization AS Shamsabadi, BML Srivastava, A Bellet, N Vauquier, E Vincent, ... Privacy Enhancing Technologies Symposium, 2022 | 36 | 2022 |
| Exploiting vulnerabilities of deep neural networks for privacy protection R Sanchez-Matilla, CY Li, AS Shamsabadi, R Mazzon, A Cavallaro IEEE Transactions on Multimedia 22 (7), 1862-1873, 2020 | 31 | 2020 |
| EdgeFool: An Adversarial Image Enhancement Filter AS Shamsabadi, C Oh, A Cavallaro 45th IEEE International Conference on Acoustics, Speech, and Signal …, 2020 | 30 | 2020 |
| PrivEdge: From Local to Distributed Private Training and Prediction AS Shamsabadi, A Gascon, H Haddadi, A Cavallaro IEEE Transactions on Information Forensics and Security (TIFS), 2020 | 27 | 2020 |
| Scene privacy protection CY Li, AS Shamsabadi, R Sanchez-Matilla, R Mazzon, A Cavallaro 44th IEEE International Conference on Acoustics, Speech and Signal …, 2019 | 26 | 2019 |
| Identifying and mitigating privacy risks stemming from language models: A survey V Smith, AS Shamsabadi, C Ashurst, A Weller arXiv preprint arXiv:2310.01424, 2023 | 23 | 2023 |
| A zest of lime: Towards architecture-independent model distances H Jia, H Chen, J Guan, AS Shamsabadi, N Papernot International Conference on Learning Representations, 2021 | 23 | 2021 |
| Privacy-preserving deep inference for rich user data on the cloud SA Osia, AS Shamsabadi, A Taheri, K Katevas, HR Rabiee, ND Lane, ... arXiv preprint arXiv:1710.01727, 2017 | 22 | 2017 |
| Washing The Unwashable: On The (Im) possibility of Fairwashing Detection AS Shamsabadi, M Yaghini, N Dullerud, S Wyllie, U Aïvodji, AAA Mkean, ... Advances in Neural Information Processing Systems, 2022 | 21 | 2022 |
| Confidential-PROFITT: Confidential PROof of FaIr Training of Trees AS Shamsabadi, SC Wyllie, N Franzese, N Dullerud, S Gambs, ... International Conference on Learning Representations, 2023 | 18 | 2023 |
| Reconstructing individual data points in federated learning hardened with differential privacy and secure aggregation F Boenisch, A Dziedzic, R Schuster, AS Shamsabadi, I Shumailov, ... 2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P), 241-257, 2023 | 15 | 2023 |
Hamed HaddadiImperial College London / Brave Software在 imperial.ac.uk 的電子郵件地址已通過驗證