| Unleashing the tiger: Inference attacks on split learning D Pasquini, G Ateniese, M Bernaschi Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications …, 2021 | 141 | 2021 |
| Eluding Secure Aggregation in Federated Learning via Model Inconsistency D Pasquini, D Francati, G Ateniese Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications …, 2022 | 88 | 2022 |
| Improving password guessing via representation learning D Pasquini, A Gangwal, G Ateniese, M Bernaschi, M Conti 2021 IEEE Symposium on Security and Privacy (SP), 1382-1399, 2021 | 84 | 2021 |
| Reducing bias in modeling real-world password strength via deep learning and dynamic dictionaries D Pasquini, M Cianfriglia, G Ateniese, M Bernaschi 30th USENIX Security Symposium (USENIX Security 21), 821-838, 2021 | 39 | 2021 |
| On the (In)security of Peer-to-Peer Decentralized Machine Learning D Pasquini, M Raynal, C Troncoso 2023 IEEE Symposium on Security and Privacy (SP), 2023 | 27* | 2023 |
| Interpretable probabilistic password strength meters via deep learning D Pasquini, G Ateniese, M Bernaschi Computer Security–ESORICS 2020: 25th European Symposium on Research in …, 2020 | 15 | 2020 |
| AMG based on compatible weighted matching for GPUs M Bernaschi, P D’Ambra, D Pasquini Parallel Computing 92, 102599, 2020 | 14 | 2020 |
| Adversarial out-domain examples for generative models D Pasquini, M Mingione, M Bernaschi 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW …, 2019 | 11 | 2019 |
| BootCMatchG: An adaptive algebraic multigrid linear solver for GPUs M Bernaschi, P D’Ambra, D Pasquini Software Impacts 6, 100041, 2020 | 6 | 2020 |
| Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks D Pasquini, M Strohmeier, C Troncoso arXiv preprint arXiv:2403.03792, 2024 | 5 | 2024 |
| Can decentralized learning be more robust than federated learning? M Raynal, D Pasquini, C Troncoso arXiv preprint arXiv:2303.03829, 2023 | 5 | 2023 |
| Universal Neural-Cracking-Machines: Self-Configurable Password Models from Auxiliary Data D Pasquini, G Ateniese, C Troncoso 2024 IEEE Symposium on Security and Privacy (SP), 2024 | 4 | 2024 |
| LLMmap: Fingerprinting for large language models D Pasquini, EM Kornaropoulos, G Ateniese arXiv preprint arXiv:2407.15847, 2024 | 1 | 2024 |
| Breach Extraction Attacks: Exposing and Addressing the Leakage in Second Generation Compromised Credential Checking Services D Pasquini, D Francati, G Ateniese, EM Kornaropoulos 2024 IEEE Symposium on Security and Privacy (SP), 2024 | | 2024 |
| Your Email Address Holds the Key: Understanding the Connection Between Email and Password Security with Deep Learning E Salimbeni, N Mainusch, D Pasquini 2023 IEEE Security and Privacy Workshops (SPW), 94-104, 2023 | | 2023 |
Giuseppe AtenieseGeorge Mason UniversityVerified email at gmu.edu
