This survey investigates current techniques for representing qualitative data for use as input
to neural networks. Techniques for using qualitative data in neural networks are well known …

Over the past few years, Internet applications have become more advanced and widely
used. This has increased the need for Internet networks to be secured. Intrusion detection …

The connectivity of devices through the internet plays a remarkable role in our daily lives.
Many network-based applications are utilized in different domains, eg, health care, smart …

This study presents a comprehensive exploration of the hyperparameter optimization in one-
dimensional (1D) convolutional neural networks (CNNs) for network intrusion detection. The …

Featured Application The model proposed in this paper can be deployed to the enterprise
gateway, dynamically monitor network activities, and connect with the firewall to protect the …

Data preprocessing is crucial in the Machine Learning pipeline because the models'
learning ability directly affects the quality of data and the underlying information acquired …

Federated Learning is an effective solution to address the issues of data isolation and
privacy leakage in machine learning. However, ensuring the security of network devices and …

Intrusion detection in computer networks is of great importance because of its effects on the
different communication and security domains. The detection of network intrusion is a …

Sign language is a natural, visually oriented and non-verbal communication channel
between people that facilitates communication through facial/bodily expressions, postures …

In recent years, computer networks have become an indispensable part of our life, and these
networks are vulnerable to various type of network attacks, compromising the security of our …