An anomaly detection apparatus for detecting data flow anomalies classes a plurality of data flows on the basis of similarity in time series changes in the data amounts of the data flows; calculates a correlation coefficient at a normal time and a correlation coefficient at a certain timing between at least two data flows belonging to the same class; and determines that at least one of the at least two data flows is anomalous when a difference between the correlation coefficient at the normal time and the correlation coefficient at the certain timing is greater than a predetermined threshold.