3 papers
cs.CR2025
EFU: Enforcing Federated Unlearning via Functional Encryption
Samaneh Mohammadi, Vasileios Tsouvalas, Iraklis Symeonidis +4
Federated unlearning (FU) algorithms allow clients in federated settings to exercise their ''right to be forgotten'' by removing the influence of their data from a collaboratively…
cs.DC2025
Empirical Analysis of Asynchronous Federated Learning on Heterogeneous Devices: Efficiency, Fairness, and Privacy Trade-offs
Samaneh Mohammadi, Iraklis Symeonidis, Ali Balador +1
Device heterogeneity poses major challenges in Federated Learning (FL), where resource-constrained clients slow down synchronous schemes that wait for all updates before aggregatio…
cs.CR2024
EncCluster: Scalable Functional Encryption in Federated Learning through Weight Clustering and Probabilistic Filters
Vasileios Tsouvalas, Samaneh Mohammadi, Ali Balador +3
Federated Learning (FL) enables model training across decentralized devices by communicating solely local model updates to an aggregation server. Although such limited data sharing…