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 …

In recent years, machine learning algorithms, and more specifically deep learning
algorithms, have been widely used in many fields, including cyber security. However …

Machine learning has witnessed tremendous growth in its adoption and advancement in the
last decade. The evolution of machine learning from traditional algorithms to modern deep …

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) …

Deep neural networks and machine-learning algorithms are pervasively used in several
applications, ranging from computer vision to computer security. In most of these …

Machine learning has become widely adopted as a strategy for dealing with a variety of
cybersecurity issues, ranging from insider threat detection to intrusion and malware …

Machine learning-based malware detection is known to be vulnerable to adversarial
evasion attacks. The state-of-the-art is that there are no effective defenses against these …

Machine learning (ML) systems have been increasingly applied in web security applications
such as spammer detection, malware detection and fraud detection. These applications …

Deep Learning algorithms have achieved state-of-the-art performance for Image
Classification. For this reason, they have been used even in security-critical applications …

Studies have shown the vulnerability of machine learning algorithms against adversarial
samples in image classification problems in deep neural networks. However, there is a need …