Abstract Machine learning (ML) techniques are increasingly important in cybersecurity, as
they can quickly analyse and identify different types of threats from millions of events. In spite …

The digital transformation has created a new digital space known as cyberspace. This new
cyberspace has improved the workings of businesses, organizations, governments, society …

This survey presents a comprehensive review of current literature on Explainable Artificial
Intelligence (XAI) methods for cyber security applications. Due to the rapid development of …

The “black-box” nature of artificial intelligence (AI) models has been the source of many
concerns in their use for critical applications. Explainable Artificial Intelligence (XAI) is a …

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 …

Cyber security is a very complex and diverse discipline. Numerous technological problems
need to be solved to make the world safer. It is evident that there is no sign of a decrease in …

Machine Learning (ML) has been widely applied to cybersecurity and is considered state-of-
the-art for solving many of the open issues in that field. However, it is very difficult to evaluate …

Explainable Artificial Intelligence (XAI) aims to improve the transparency of machine
learning (ML) pipelines. We systematize the increasingly growing (but fragmented) …

Information about cyber-attack planning has been increasingly shared by malicious hackers
online, making what was once a hard-to-penetrate market becomes accessible to a wider …

Nowadays, Artificial Intelligence (AI) is widely applied in every area of human being's daily
life. Despite the AI benefits, its application suffers from the opacity of complex internal …