Federated learning (FL) is a distributed machine learning (ML) approach that enables
models to be trained on client devices while ensuring the privacy of user data. Model …

The deployment of the fifth-generation (5G) wireless networks in Internet of Everything (IoE)
applications and future networks (eg, sixth-generation (6G) networks) has raised a number …

Cloud computing has gained popularity in recent years, but with its rise comes concerns
about data security. Unauthorized access and attacks on cloud-based data, applications …

In order to optimize the deployment of wireless sensor network nodes, and avoid network
energy consumption increase due to node redundancy and uneven coverage, the multi …

The distributed architecture of cloud computing necessitates robust defense mechanisms to
secure network-accessible resources against a diverse and dynamic threat landscape. A …

The identification of immature apples is a key technical link to realize automatic real-time
monitoring of orchards, expert decision-making, and realization of orchard output prediction …

In recent years, federated learning has been applied to the security of the Internet of Things
and Industrial Control Systems (ICS) due to its advantages in communication cost and …

In today's world, it is vital to have strong cybersecurity measures in place. To combat the
ever-evolving threats, adopting advanced models like cybersecurity mesh is necessary to …

The rapid expansion of Internet of Things (IoT) devices presents unique challenges in
ensuring the security and privacy of interconnected systems. As cyberattacks become more …

As reducing carbon emissions can relieve environmental concerns, networks-supported
renewable power plants are being built more and more. Inevitable network attacks have …