In a wide range of industries and academic fields, artificial intelligence is becoming
increasingly prevalent. AI models are taking on more crucial decision-making tasks as they …

The problem of malicious software (malware) detection and classification is a complex task,
and there is no perfect approach. There is still a lot of work to be done. Unlike most other …

Augmented and Virtual Reality (AR and VR), collectively known as Extended Reality (XR),
are increasingly gaining traction thanks to their technical advancement and the need for …

Abstract Machine Learning (ML)-based network intrusion detection systems bring many
benefits for enhancing the cybersecurity posture of an organisation. Many systems have …

Explainability is increasingly recognized as an enabling technology for the broader adoption
of machine learning (ML), particularly for safety-critical applications. This has given rise to …

The growing number of applications of machine learning and data mining in many domains—
from agriculture to business, education, industrial manufacturing, and medicine—gave rise …

Synthetically generated benchmark datasets are vitally important for machine learning and
network intrusion research. When producing intrusion datasets for research, providers make …

Significant efforts have been investigated to develop machine learning (ML) based tools to
support security operations. However, they still face key challenges in practice. A generally …

In this research, we explore the nexus between artificial intelligence (AI) and blockchain, two
paramount forces steering the contemporary digital era. AI, replicating human cognitive …

The remarkable achievements of Artificial Intelligence (AI) algorithms, particularly in
Machine Learning (ML) and Deep Learning (DL), have fueled their extensive deployment …