149 citations · 149 across the 3 of their papers we have counts for
3 papers
Membership Inference Attacks fueled by Few-Short Learning to detect privacy leakage tackling data integrity
Daniel Jiménez-López, Nuria Rodríguez-Barroso, M. Victoria Luzón +1
Deep learning models have an intrinsic privacy issue as they memorize parts of their training data, creating a privacy leakage. Membership Inference Attacks (MIA) exploit it to obt…
FLEX: FLEXible Federated Learning Framework
Francisco Herrera, Daniel Jiménez-López, Alberto Argente-Garrido +6
In the realm of Artificial Intelligence (AI), the need for privacy and security in data processing has become paramount. As AI applications continue to expand, the collection and h…
Federated Learning and Differential Privacy: Software tools analysis, the Sherpa.ai FL framework and methodological guidelines for preserving data privacy
Nuria Rodríguez-Barroso, Goran Stipcich, Daniel Jiménez-López +6
The high demand of artificial intelligence services at the edges that also preserve data privacy has pushed the research on novel machine learning paradigms that fit those requirem…