3 citations · 3 across the 10 of their papers we have counts for
4 papers · 1 filter
On Local Mutual-Information Privacy
Khac-Hoang Ngo, Johan Östman, Alexandre Graell i Amat
Local mutual-information privacy (LMIP) is a privacy notion that aims to quantify the reduction of uncertainty about the input data when the output of a privacy-preserving mechanis…
Timely Status Updates in Slotted ALOHA Networks With Energy Harvesting
Khac-Hoang Ngo, Giuseppe Durisi, Andrea Munari +2
We investigate the age of information (AoI) in a scenario where energy-harvesting devices send status updates to a gateway following the slotted ALOHA protocol and receive no feedb…
Secure Aggregation is Not Private Against Membership Inference Attacks
Khac-Hoang Ngo, Johan Östman, Giuseppe Durisi +1
Secure aggregation (SecAgg) is a commonly-used privacy-enhancing mechanism in federated learning, affording the server access only to the aggregate of model updates while safeguard…
Decoupled Subgraph Federated Learning
Javad Aliakbari, Johan Östman, Alexandre Graell i Amat
We address the challenge of federated learning on graph-structured data distributed across multiple clients. Specifically, we focus on the prevalent scenario of interconnected subg…