| 2026 | SP | Know-It-All?: A Human-Calibrated LLM Benchmark for Cybersecurity Knowledge. | Athanasios Theocharis, Armin Buescher, Omer Akgul, Dario Pasquini, Oystein Fladby, Daniel Marino, Christopher Gates, Petros Efstathopoulos |
| 2024 | SP | Universal Neural-Cracking-Machines: Self-Configurable Password Models from Auxiliary Data. | Dario Pasquini, Giuseppe Ateniese, Carmela Troncoso |
| 2024 | SP | Breach Extraction Attacks: Exposing and Addressing the Leakage in Second Generation Compromised Credential Checking Services. | Dario Pasquini, Danilo Francati, Giuseppe Ateniese, Evgenios M. Kornaropoulos |
| 2023 | SP | On the (In)security of Peer-to-Peer Decentralized Machine Learning. | Dario Pasquini, Mathilde Raynal, Carmela Troncoso |
| 2023 | SP | Your Email Address Holds the Key: Understanding the Connection Between Email and Password Security with Deep Learning. | Etienne Salimbeni, Nina Mainusch, Dario Pasquini |
| 2022 | CCS | Eluding Secure Aggregation in Federated Learning via Model Inconsistency. | Dario Pasquini, Danilo Francati, Giuseppe Ateniese |
| 2021 | CCS | Unleashing the Tiger: Inference Attacks on Split Learning. | Dario Pasquini, Giuseppe Ateniese, Massimo Bernaschi |
| 2021 | SP | Improving Password Guessing via Representation Learning. | Dario Pasquini, Ankit Gangwal, Giuseppe Ateniese, Massimo Bernaschi, Mauro Conti |
| 2020 | ESORICS | Interpretable Probabilistic Password Strength Meters via Deep Learning. | Dario Pasquini, Giuseppe Ateniese, Massimo Bernaschi |