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. By establishing a baseline of normal activity, this approach can flag any significant deviations that may indicate potential threats or issues. This technique is particularly useful for detecting intrusions or fraud, as it can uncover new or unknown threats that traditional methods might miss. Anomaly-based systems continuously learn and adapt, improving their ability to recognize legitimate anomalies over time, thus enhancing overall security and efficiency.