Anomaly Detection in Security

Anomaly detection in security refers to the process of identifying unusual patterns or behaviors that deviate from the norm within a system or network. This technique is crucial for detecting potential security threats, such as intrusions, fraud, or system malfunctions. By leveraging machine learning algorithms and statistical methods, anomaly detection systems can analyze vast amounts of data to identify subtle changes that may indicate a security breach. Common use cases include monitoring network traffic, user behavior analytics, and identifying vulnerabilities in software applications.