162 citations · 883 across the 43 of their papers we have counts for
5 papers · 1 filter
Achieving Security and Privacy in Federated Learning Systems: Survey, Research Challenges and Future Directions
Alberto Blanco-Justicia, Josep Domingo-Ferrer, Sergio Martínez +3
Federated learning (FL) allows a server to learn a machine learning (ML) model across multiple decentralized clients that privately store their own training data. In contrast with…
The Limits of Differential Privacy (and its Misuse in Data Release and Machine Learning)
Josep Domingo-Ferrer, David Sánchez, Alberto Blanco-Justicia
Differential privacy (DP) is a neat privacy definition that can co-exist with certain well-defined data uses in the context of interactive queries. However, DP is neither a silver…
General Confidentiality and Utility Metrics for Privacy-Preserving Data Publishing Based on the Permutation Model
Josep Domingo-Ferrer, Krishnamurty Muralidhar, Maria Bras-Amorós
Anonymization for privacy-preserving data publishing, also known as statistical disclosure control (SDC), can be viewed under the lens of the permutation model. According to this m…
Multi-Dimensional Randomized Response
Josep Domingo-Ferrer, Jordi Soria-Comas
In our data world, a host of not necessarily trusted controllers gather data on individual subjects. To preserve her privacy and, more generally, her informational self-determinati…
Give more data, awareness and control to individual citizens, and they will help COVID-19 containment
Mirco Nanni, Gennady Andrienko, Albert-László Barabási +36
The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the phase 2 of the pandemic, when…