5 papers
SoK: Rethinking Membership Inference in Tabular Machine Learning
Cristina Pêra, Tânia Carvalho, Maxime Cordy +1
Membership Inference Attacks (MIAs) are currently the dominant approach to evaluating privacy in machine learning applications. Despite their significance, several concerns remain…
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…