In the realm of machine learning (ML) systems featuring client-host connections, the
enhancement of privacy security can be effectively achieved through federated learning (FL) …

Millions of vulnerable consumer IoT devices in home networks are the enabler for cyber
crimes putting user privacy and Internet security at risk. Internet service providers (ISPs) are …

The Internet of Things (IoT) has revolutionized our lives by generating large amounts of data,
however, the data needs to be collected, processed, and analyzed in real-time. Network …

The increasing prevalence of botnet attacks in IoT networks has led to the development of
deep learning techniques for their detection. However, conventional centralized deep …

The exponential growth of internet traffic causes significant challenges for network traffic
classification, such as maintaining data privacy and requiring more computing resources. To …

Network traffic classification is vital for network security. However, the non-IID nature of
participant data poses challenges for federated learning in this context. This study examines …