METHOD FOR DETECTING ANOMALIES IN TIME SERIES DATA PRODUCED BY DEVICES OF AN INFRASTRUCTURE IN A NETWORK

The present invention relates to a method for detecting anomalies in time series data produced by devices of an infrastructure in a network comprising, for each of the devices through computerized data processing means, retrieving a time series data for the device in the network, extracting a plurality of time series samples relating to respective time windows and having a predefined window size and a predefined stride, by sliding the time windows to overlap the time series data, supplying the time series samples as input to a Convolutional Autoencoder to define reconstructed time series values having a predefined percentile intervals, analysing the reconstructed time series values to identify anomalous behaviours of the time series data, signalling an anomaly of the device when at least one anomalous behaviour is identified.