There is an increase in cyberattacks directed at the network behind firewalls. An all-inclusive
approach is proposed in this assessment to deal with the problem of identifying new …

In recent years, significant progress has been made in the application of federated learning
(FL) in various aspects of cyberspace security, such as intrusion detection, privacy …

A bilevel programming model represents the relationship in a specific decision process that
involves decisions within a hierarchical structure of two levels. The upper-level problem is …

Industrial automation systems are undergoing a revolutionary change with the use of
Internet-connected operating equipment and the adoption of cutting-edge advanced …

Federated bilevel optimization (FBO) has shown great potential recently in machine learning
and edge computing due to the emerging nested optimization structure in meta-learning …

Data augmentation is one of the most important problems in deep learning. There have
been many algorithms proposed to solve this problem, such as simple noise injection, the …

Deep neural network-based autoencoders can effectively extract high-level abstract features
with outstanding generalization performance but suffer from sparsity of extracted features …

Mobile edge computing (MEC) enables the Internet of Things (IoT) with seamless integration
of multiple application services. Federated learning is increasingly considered to improve …

Most studies have conducted experiments on predicting energy consumption by integrating
data for model training. However, the process of centralizing data can cause problems of …

Abstract Recently, Vehicular Ad-hoc Network (VANET) has been one of the emerging fields
of research. Many researchers are doing their research on various challenges of VANET …