The adoption of machine learning (ML) and, more specifically, deep learning (DL)
applications into all major areas of our lives is underway. The development of trustworthy AI …

Context: Research at the intersection of cybersecurity, Machine Learning (ML), and Software
Engineering (SE) has recently taken significant steps in proposing countermeasures for …

Machine Learning (ML) represents a pivotal technology for current and future information
systems, and many domains already leverage the capabilities of ML. However, deployment …

Phishing email attack is a dominant cyber-criminal strategy for decades. Despite its
longevity, it has evolved during the COVID-19 pandemic, indicating that adversaries exploit …

This article aims to analyze the current unpredictable cyber climate. In particular, Russia's
invasion of Ukraine has heightened concerns about security incidents, and ransomware …

Machine learning (ML) has become an important paradigm for cyberthreat detection (CTD)
in the recent years. A substantial research effort has been invested in the development of …

Phishing, a well-known cyber-attack practice has gained significant research attention in the
cyber-security domain for the last two decades due to its dynamic attacking strategies …

In this survey, we review the key developments in the field of malware detection using AI and
analyze core challenges. We systematically survey state-of-the-art methods across five …

Phishing is the most-used malicious attempt in which attackers, commonly via emails,
impersonate trusted persons or entities to obtain private information from a victim. Even …

The surge of constantly evolving network attacks can be addressed by designing an
effective and efficient Intrusion Detection System (IDS). Various Deep Learning (DL) …