Context aware anomaly detection

A computer program product for context aware anomaly detection, the computer program product comprising:

• one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instructions comprising:
• program instructions to receive a signal including real-time data;
• program instructions to divide the received signal into a set of training wavelets bounded by a respective training context;
• program instructions to generate 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;
• program instructions to, in response to execution of a current context that is different from the training context, extract current wavelets from a signal of the current context;
• program instructions to identify 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;
• and
• program instructions to identify an anomaly in response to determining that a total cumulative distance between the two sequences exceeds a predetermined threshold.

A computer-implemented method of identifying a context, the method comprising:

• receiving real-time data of the context over a time period;
• setting the context to a first level of granularity;
• dividing the real-time data into wavelets based on the first level of granularity;
• and
• attempting to identify a pattern in the wavelets based on dynamic time warping.