In recent years, mobile devices are equipped with increasingly advanced sensing and
computing capabilities. Coupled with advancements in Deep Learning (DL), this opens up …

This paper provides a comprehensive study of Federated Learning (FL) with an emphasis
on enabling software and hardware platforms, protocols, real-life applications and use …

Federated learning (FL) is a rapidly growing research field in machine learning. However,
existing FL libraries cannot adequately support diverse algorithmic development; …

Federated learning promises to use the computational power of edge devices while
maintaining user data privacy. Current frameworks, however, typically make the unrealistic …

In this paper we present LiM (" Less is More"), a malware classification framework that
leverages Federated Learning to detect and classify malicious apps in a privacy-respecting …