Anomaly-based detection is a method used in various fields, including cybersecurity and data analysis, to identify unusual patterns or behaviors that deviate from the norm. This approach relies on establishing a baseline of normal activity, allowing systems to flag any significant deviations that may indicate potential threats or issues. In cybersecurity, for example, anomaly-based systems monitor network traffic and user behavior to detect suspicious activities, such as unauthorized access or data breaches. By focusing on anomalies rather than known threats, these systems can identify new and evolving risks that traditional signature-based methods might miss.