Device for Clustering-based Labeling, Device for Anomaly Detection, and Methods therefor

A device for performing labeling, the device comprising:

• a cluster unit, upon receiving a plurality of input data, forming a plurality of nodes by mapping the plurality of input data into a predetermined vector space, and creating a cluster by clustering the plurality of nodes;
• and
• a label processor deriving one or more connected components by performing connected component analysis on the created cluster, and performing labeling on the connected components.

A device for anomaly detection, the device comprising:

• a cluster unit creating a data cluster by clustering accumulated data whenever a predetermined first number of input data are accumulated;
• and
• a detection unit inputting the data cluster into a detection network trained to simulate the data cluster, when the detection network reconstructs the data cluster and creates a simulated data cluster simulating the data cluster, determining whether a difference between the simulated data cluster and the input data cluster is greater than or equal to a predetermined threshold, and upon determining that the difference is greater than or equal to the predetermined threshold, determining that there is an anomaly in the input data cluster.