4 papers
Privacy Vulnerabilities of Attention Layers in Tabular Foundation Models and Protection of High-Risk Queries
Tânia Carvalho, Maxime Cordy
Tabular foundation models are commonly assumed to present limited privacy concerns as they are often pre-trained on large collections of synthetic data. However, these models lever…
SoK: Challenges in Tabular Membership Inference Attacks
Cristina Pêra, Tânia Carvalho, Maxime Cordy +1
Membership Inference Attacks (MIAs) are currently a dominant approach for evaluating privacy in machine learning applications. Despite their significance in identifying records bel…
Privacy-Driven Network Data for Smart Cities
Tânia Carvalho, José Barata, Henish Balu +3
A smart city is essential for sustainable urban development. In addition to citizen engagement, a smart city enables connected infrastructure, data-driven decision making and smart…
Secure Visual Data Processing via Federated Learning
Pedro Santos, Tânia Carvalho, Filipe Magalhães +1
As the demand for privacy in visual data management grows, safeguarding sensitive information has become a critical challenge. This paper addresses the need for privacy-preserving…