| CPC G06N 3/08 (2013.01) [G06N 3/04 (2013.01); H04L 63/20 (2013.01)] | 20 Claims |
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1. A method to continuously classify temporal communication data associated with a computing device, the method comprising:
accessing temporal communication data associated with the computing device;
vectorizing the temporal communication data to generate one or more feature vectors, wherein the vectorizing includes converting one or more words in the temporal communication data to a vectorized form while preserving a semantic relationship between the words;
performing one or more vector averaging and vector normalization operations on the feature vectors;
combining the averaged and normalized feature vectors to generate a feature matrix;
further processing the temporal communication data to generate a plurality of preprocessing models, wherein at least one preprocessing model in the plurality of preprocessing models includes the feature matrix;
training, using data generated by the preprocessing models, a neural network;
deriving, by the neural network, one or more properties associated with the computing device from the temporal communication data;
defining, a device fingerprint from the one or more properties;
subsequent to defining the device fingerprint, accessing additional temporal communication data associated with the computing device;
deriving, by the neural network, one or more additional properties associated with the computing device from the additional temporal communication data; and
aggregating the one or more additional properties into the defined device fingerprint refining the defined device fingerprint.
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