Sliding window anomaly detection is a technique used in cybersecurity to identify unusual patterns or behaviors that deviate from the norm. It involves analyzing segments of data over a period of time, referred to as a 'window,' and comparing them against typical patterns. Anomalies are detected when observed behaviors significantly differ from expected patterns, indicating potential security incidents or issues that require further investigation. References: An adaptive sliding window for anomaly detection of time series in wireless sensor networks