An anomaly detection method includes: calculating, for a detection target data stream of consecutive detection target data, distances between the detection target data; extracting features of the detection target data stream using the calculated distances; and calculating anomaly degree information about a degree of anomaly in the detection target data stream using the extracted features. Each extracted feature is made up of L consecutive distances (L is an integer greater than or equal to 2). For each feature extracted, supplementary information for calculating the anomaly degree information is calculated using a difference in the feature. For each of one or more information calculation target windows made up of N detection target data (N is an integer greater than or equal to L+1), the anomaly degree information is calculated using all supplementary information calculated from the N detection target data.