In an embodiment, a method includes: using at least two items of sequentially collected, mutually associated data to create at least two detection data sets, each including a first number of items of sequentially collected data in the at least two items of data; using an autoencoder to process the at least two detection data sets, to output result data sets respectively corresponding to the at least two detection data sets, the first number being equal to the number of neurons in an input layer of the autoencoder, and the autoencoder being trained using data having a regular pattern of variation identical to the at least two items of data; and determining, as abnormal data, data which does not have the regular pattern of variation in the at least two items of data, based upon the at least two detection data sets and the result data sets corresponding thereto.