Machine learning is of rising importance in cybersecurity. The primary objective of applying
machine learning in cybersecurity is to make the process of malware detection more …

The exponential advancements in processing, storage and network technologies have led to
the recent explosive growth in big data, connectivity and machine learning. The world is …

In the rapidly evolving landscape of cybersecurity, the proliferation of sophisticated threats
necessitates innovative approaches for detection and prevention. Machine learning …

Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …

This book introduces various machine learning methods for cyber security analytics. With an
overwhelming amount of data being generated and transferred over various networks …

Cyberspace has grown due to the widespread uses of the Internets and mobiles apps.
Attacks on the Internet are more likely to be automated and to last longer. Cyber security …

In the ever-evolving landscape of cybersecurity, the effective detection of threats is
paramount to safeguarding digital assets and privacy. This research article presents a …

This is a systematic review of over one hundred research papers about machine learning
methods applied to defensive and offensive cybersecurity. In contrast to previous reviews …

Machine learning (ML) and deep learning (DL) both drawn unparalleled community interest
recently. With a growing convergence of online activities and digital life, the way people …

Can machine learning techniques solve our computer security problems and finally put an
end to the cat-and-mouse game between attackers and defenders? Or is this hope merely …