Deep learning (DL) is an efficient method for botnet attack detection. However, the volume of
network traffic data and memory space required is usually large. It is, therefore, almost …

Networks had an increasing impact on modern life since network cybersecurity has become
an important research field. Several machine learning techniques have been developed to …

This paper concerns cybersecurity issues in one of the fastest growing fields of modern
computer systems the Internet-of-Things (IoT). In this field, intrusion detection plays a …

This paper proposes a semi-supervised autoencoder with an auxiliary task (SAAT) to extract
a health feature space for power transformer fault diagnosis using dissolved gas analysis …

The increase in the deployment of IOT networks has improved productivity of humans and
organisations. However, IOT networks are increasingly becoming platforms for launching …

Various applications in remote sensing demand automatic detection of changes in optical
satellite images of the same scene acquired over time. This paper investigates how to …

As the 5G rolls out around the world, many edge applications will be deployed by app
vendors and accessed by massive end-users. Efficient detection of malicious network …

This research presents a novel combined learning method for developing a novel DDoS
model that is expandable and flexible property of deep learning. This method can advance …

Quotidian, the perspective of cyber attacks. New malware divergent are provoked almost
daily, the number of attacks is up by 56%. Many see cyber-security alliterative in the form of …

Machine learning is a branch of artificial intelligence that provides computers the ability to
create or improve algorithms without being explicitly programmed by directly learning from …