About me:
- Current status: Post-doc at EPFL (Spring lab), "Collaborative Machine Learning skeptic", and "honest-but-curious security model unbeliever". Working on:
- Security and Privacy in Machine Learning (Collaborative Machine Learning mainly).
- Password Security.
HPC, GPGPU.
News:
- 👔 Looking for a position in industry.
Preprints:
Recent publications:
- [IEEE S&P '23] - Dario Pasquini, Mathilde Raynal, Carmela Troncoso.
On the (In)security of Peer-to-Peer Decentralized Machine Learning.
- [ACM CCS '22] - Dario Pasquini, Danilo Francati, Giuseppe Ateniese.
Eluding Secure Aggregation in Federated Learning via Model Inconsistency.
-
[ACM CCS '21] - Dario Pasquini, Giuseppe Ateniese, Massimo Bernaschi.
Unleashing the Tiger: Inference Attacks on Split Learning.
-
[USENIX Sec '21] - Dario Pasquini, Marco Cianfriglia, Giuseppe Ateniese, Massimo Bernaschi.
Reducing Bias in Modeling Real-world Password Strength via Deep Learning and Dynamic Dictionaries.
-
[IEEE S&P '21] - Dario Pasquini, Ankit Gangwal, Giuseppe Ateniese, Massimo Bernaschi, Mauro Conti.
Improving Password Guessing via Representation Learning.
Program Committees: