12 citations · 13 across the 5 of their papers we have counts for
5 papers
Pushing Forward Multi-Secret-Key Homomorphic Encryption for Private Average Aggregation
Miguel Morona-Mínguez, Fernando Pérez-González, Alberto Pedrouzo-Ulloa
Federated Learning enables multiple clients to train a shared model while keeping their local datasets isolated. However, the exchanged model updates may still leak sensitive infor…
A Critical Look into Threshold Homomorphic Encryption for Private Average Aggregation
Miguel Morona-Mínguez, Alberto Pedrouzo-Ulloa, Fernando Pérez-González
Threshold Homomorphic Encryption (Threshold HE) is a good fit for implementing private federated average aggregation, a key operation in Federated Learning (FL). Despite its potent…
BlackCATT: Black-box Collusion Aware Traitor Tracing in Federated Learning
Elena Rodríguez-Lois, Fabio Brau, Maura Pintor +2
Federated Learning has been popularized in recent years for applications involving personal or sensitive data, as it allows the collaborative training of machine learning models th…
Exploring Federated Learning Dynamics for Black-and-White-Box DNN Traitor Tracing
Elena Rodriguez-Lois, Fernando Perez-Gonzalez
As deep learning applications become more prevalent, the need for extensive training examples raises concerns for sensitive, personal, or proprietary data. To overcome this, Federa…
An Adaptive Method for Camera Attribution under Complex Radial Distortion Corrections
Andrea Montibeller, Fernando Pérez-González
Radial correction distortion, applied by in-camera or out-camera software/firmware alters the supporting grid of the image so as to hamper PRNU-based camera attribution. Existing s…