International Business Machines Corporation
CONTEXT AWARE ANOMALY DETECTION

Abstract:

A computer-implemented method for context aware anomaly detection includes receiving a signal including real-time data, dividing the received signal into a set of training wavelets bounded by a respective training context, generating a prediction model for the training context by processing the set of training wavelets through a recurrent neural network to identify patterns in a sequence of data of a respective training wavelet. The method includes, in response to execution of a current context that is different from the training context, extracting current wavelets from a signal of the current context, identifying a pairwise match between same dimensions of the current wavelets and a wavelet pattern of the prediction model by aligning sequences of the current wavelet and sequences of the wavelet pattern of the prediction model. Upon determining that a total cumulative distance between the two sequences exceeds a predetermined threshold, an anomaly is identified.