Machine Learning (ML) in Security is the application of machine learning algorithms to the field of cybersecurity.
ML in security can be used to detect and respond to malicious activity on networks, detect system vulnerabilities, and identify anomalous user behavior. ML algorithms are able to analyze large amounts of data and identify patterns and trends that would be difficult for humans to detect. This can help security teams identify threats and respond to them quickly and accurately. ML can also be used to automate security processes, such as user authentication and authorization, to reduce the amount of manual work required by security teams. ML can also be used to detect and respond to advanced persistent threats (APTs) and other sophisticated attacks. ML can also be used to detect insider threats and protect sensitive data.