3 papers
cs.CR2024
ACCESS-FL: Agile Communication and Computation for Efficient Secure Aggregation in Stable Federated Learning Networks
Niousha Nazemi, Omid Tavallaie, Shuaijun Chen +5
Federated Learning (FL) is a promising distributed learning framework designed for privacy-aware applications. FL trains models on client devices without sharing the client's data…
cs.NI2024
Analysis of DNS Dependencies and their Security Implications in Australia: A Comparative Study of General and Indigenous Populations
Niousha Nazemi, Omid Tavallaie, Anna Maria Mandalari +3
This paper investigates the impact of internet centralization on DNS provisioning, particularly its effects on vulnerable populations such as the indigenous people of Australia. We…
cs.CR2024
Boosting Communication Efficiency of Federated Learning's Secure Aggregation
Niousha Nazemi, Omid Tavallaie, Shuaijun Chen +2
Federated Learning (FL) is a decentralized machine learning approach where client devices train models locally and send them to a server that performs aggregation to generate a glo…