30 citations · 90 across the 12 of their papers we have counts for
6 papers · 1 filter
Giskard : Byzantine Robust and Private Aggregation for Large-Scale Decentralized Learning
Ousmane Touat, César Sabater, Mohamed Maouche +1
In decentralized learning, clients train a machine learning model while keeping their data locally and share their model parameters or gradients with a set of neighbors, making it…
TEE-based Key-Value Stores: a Survey
Aghiles Ait Messaoud, Sonia Ben Mokhtar, Anthony Simonet-Boulogne
Key-Value Stores (KVSs) are No-SQL databases that store data as key-value pairs and have gained popularity due to their simplicity, scalability, and fast retrieval capabilities. Ho…
Shielding Federated Learning Systems against Inference Attacks with ARM TrustZone
Aghiles Ait Messaoud, Sonia Ben Mokhtar, Vlad Nitu +1
Federated Learning (FL) opens new perspectives for training machine learning models while keeping personal data on the users premises. Specifically, in FL, models are trained on th…
Adaptive Location Privacy with ALP
Vincent Primault, Antoine Boutet, Sonia Ben Mokhtar +1
With the increasing amount of mobility data being collected on a daily basis by location-based services (LBSs) comes a new range of threats for users, related to the over-sharing o…
Privacy-preserving Publication of Mobility Data with High Utility
Vincent Primault, Sonia Ben Mokhtar, Lionel Brunie
An increasing amount of mobility data is being collected every day by different means, e.g., by mobile phone operators. This data is sometimes published after the application of si…
Differentially Private Location Privacy in Practice
Vincent Primault, Sonia Ben Mokhtar, Cedric Lauradoux +1
With the wide adoption of handheld devices (e.g. smartphones, tablets) a large number of location-based services (also called LBSs) have flourished providing mobile users with real…