6 papers
Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution
Gabriele Digregorio, Marco Di Gennaro, Francesco Pastore +3
The growing reliance on pre-trained Machine Learning (ML) models has introduced new attack surfaces. Recent vulnerabilities demonstrate that malicious behavior can be embedded with…
On the (In)Security of Loading Machine Learning Models
Gabriele Digregorio, Marco Di Gennaro, Stefano Zanero +2
The rise of model sharing through frameworks and dedicated hubs makes Machine Learning significantly more accessible. Despite its benefits, loading shared models exposes users to u…
TimberStrike: Dataset Reconstruction Attack Revealing Privacy Leakage in Federated Tree-Based Systems
Marco Di Gennaro, Giovanni De Lucia, Stefano Longari +2
Federated Learning has emerged as a privacy-oriented alternative to centralized Machine Learning, enabling collaborative model training without direct data sharing. While extensive…
PackHero: A Scalable Graph-based Approach for Efficient Packer Identification
Marco Di Gennaro, Mario D'Onghia, Mario Polino +2
Anti-analysis techniques, particularly packing, challenge malware analysts, making packer identification fundamental. Existing packer identifiers have significant limitations: sign…
Amatriciana: Exploiting Temporal GNNs for Robust and Efficient Money Laundering Detection
Marco Di Gennaro, Francesco Panebianco, Marco Pianta +2
Money laundering is a financial crime that poses a serious threat to financial integrity and social security. The growing number of transactions makes it necessary to use automatic…
A Federated Learning Platform as a Service for Advancing Stroke Management in European Clinical Centers
Diogo Reis Santos, Albert Sund Aillet, Antonio Boiano +10
The rapid evolution of artificial intelligence (AI) technologies holds transformative potential for the healthcare sector. In critical situations requiring immediate decision-makin…