Machine learning in cybersecurity: A review

Machine learning technology has become mainstream in a large number of domains, and cybersecurity applications of machine learning techniques are plenty. Examples include malware analysis, especially for zero-day malware detection, threat analysis, anomaly based intrusion detection of prevalent attacks on critical infrastructures, and many others. Due to the ineffectiveness of signature-based methods in detecting zero day attacks or even slight variants of known attacks, machine learning-based detection is being used by researchers in many cybersecurity products. In this review, we discuss several areas of cybersecurity where machine learning is used as a tool. We also provide a few glimpses of adversarial attacks on machine learning algorithms to manipulate training and test data of classifiers, to render such tools ineffective. This article is categorized under: Application Areas > Science and Technology Technologies > Machine Learning Technologies > Classification Application Areas > Data Mining Software Tools