Abstract Recently, numerous Machine Learning (ML) algorithms have been applied in many
areas of cybersecurity. However, most of these systems can only be seen as a black box to …

Despite the growing popularity of modern machine learning techniques (eg, Deep Neural
Networks) in cyber-security applications, most of these models are perceived as a black-box …

Cyber-security is the practice of protecting computing systems and networks from digital
attacks, which are a rising concern in the Information Age. With the growing pace at which …

Today's world is highly network interconnected owing to the pervasiveness of small personal
devices (eg, smartphones) as well as large computing devices or services (eg, cloud …

Machine Learning (ML) algorithms, specifically supervised learning, are widely used in
modern real-world applications, which utilize Computational Intelligence (CI) as their core …

Cyber security is used to protect and safeguard computers and various networks from ill-
intended digital threats and attacks. It is getting more difficult in the information age due to …

In recent years, machine learning (ML) has become an important part to yield security and
privacy in various applications. ML is used to address serious issues such as real-time …

Concerns about cybersecurity and attack methods have risen in the information age. Many
techniques are used to detect or deter attacks, such as intrusion detection systems (IDSs) …

Machine-learning solutions are successfully adopted in multiple contexts but the application
of these techniques to the cyber security domain is complex and still immature. Among the …

Machine learning technology has become mainstream in a large number of domains, and
cybersecurity applications of machine learning techniques are plenty. Examples include …