47 citations · 214 across the 25 of their papers we have counts for
10 papers · 1 filter
Crypto'Graph: Leveraging Privacy-Preserving Distributed Link Prediction for Robust Graph Learning
Sofiane Azogagh, Zelma Aubin Birba, Sébastien Gambs +1
Graphs are a widely used data structure for collecting and analyzing relational data. However, when the graph structure is distributed across several parties, its analysis is parti…
Frequency Estimation of Evolving Data Under Local Differential Privacy
Héber H. Arcolezi, Carlos Pinzón, Catuscia Palamidessi +1
Collecting and analyzing evolving longitudinal data has become a common practice. One possible approach to protect the users' privacy in this context is to use local differential p…
On the Risks of Collecting Multidimensional Data Under Local Differential Privacy
Héber H. Arcolezi, Sébastien Gambs, Jean-François Couchot +1
The private collection of multiple statistics from a population is a fundamental statistical problem. One possible approach to realize this is to rely on the local model of differe…
Multi-Freq-LDPy: Multiple Frequency Estimation Under Local Differential Privacy in Python
Héber H. Arcolezi, Jean-François Couchot, Sébastien Gambs +2
This paper introduces the multi-freq-ldpy Python package for multiple frequency estimation under Local Differential Privacy (LDP) guarantees. LDP is a gold standard for achieving l…
Online publication of court records: circumventing the privacy-transparency trade-off
Tristan Allard, Louis Béziaud, Sébastien Gambs
The open data movement is leading to the massive publishing of court records online, increasing transparency and accessibility of justice, and to the design of legal technologies b…
DYSAN: Dynamically sanitizing motion sensor data against sensitive inferences through adversarial networks
Claude Rosin Ngueveu, Antoine Boutet, Carole Frindel +3
With the widespread adoption of the quantified self movement, an increasing number of users rely on mobile applications to monitor their physical activity through their smartphones…