CPC H04L 63/1416 (2013.01) [H04L 63/1425 (2013.01); H04L 63/1441 (2013.01)] | 20 Claims |
1. A method, comprising:
converting, via a processor, a plurality of sets of events associated with a first device into a time series, each set of events from the plurality of sets of events associated with the first device and a second device from a plurality of second devices that is different for remaining sets of events from the plurality of sets of events and does not include the first device;
performing, via the processor, a discrete Fourier transform based on the time series to generate an output, wherein performing the discrete Fourier transform includes:
normalizing the time series to generate a normalized time series;
calculating, using the normalized time series, a linear regression fit that includes indication of a slope and an intercept;
subtracting the slope and the intercept from the normalized time series to generate a modified normalized time series;
applying a hamming window to the normalized time series to generate an input; and
generating the output based on inputting the input to the discrete Fourier transform;
identifying, via the processor and based on the output, an attribute associated with an event from a set of events from the plurality of sets of events that is predicted to cause a periodic behavior; and
sending, via the processor, a signal to cause an output including representation of the attribute.
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