6. A computer implemented method for tokenization of data, the method comprising the steps of: receiving a request for tokenization, wherein the request comprises input data to be tokenized; parsing the input data into a plurality of input data parts and determining respective datatypes corresponding to the input data parts; generating, by a trained artificial neural network executing on one or more computing devices and configured to generate tokens via a plurality of different tokenization techniques, at least one output token corresponding to a given input data part out of the plurality of input data parts via a secure tokenization technique corresponding to the datatype of the given input data part, wherein the trained artificial neural network comprises a feed-forward neural network having a forward direction and a backward direction, and comprising an input layer, an output layer, and one or more hidden layers that apply a transformation to the plurality of input data parts and respective datatypes to generate the tokens via the plurality of different tokenization techniques; receiving a system input; and converting the at least one output token back to the given input data part with the system input, wherein the secure tokenization technique does not allow the at least one output token to be converted back to the given input data part without the system input.
6. A computer implemented method for tokenization of data, the method comprising the steps of: receiving a request for tokenization, wherein the request comprises input data to be tokenized; parsing the input data into a plurality of input data parts and determining respective datatypes corresponding to the input data parts; generating, by a trained artificial neural network executing on one or more computing devices and configured to generate tokens via a plurality of different tokenization techniques, at least one output token corresponding to a given input data part out of the plurality of input data parts via a secure tokenization technique corresponding to the datatype of the given input data part, wherein the trained artificial neural network comprises a feed-forward neural network having a forward direction and a backward direction, and comprising an input layer, an output layer, and one or more hidden layers that apply a transformation to the plurality of input data parts and respective datatypes to generate the tokens via the plurality of different tokenization techniques; receiving a system input; and converting the at least one output token back to the given input data part with the system input, wherein the secure tokenization technique does not allow the at least one output token to be converted back to the given input data part without the system input. 7. The method of claim 6 , further comprising storing the at least one output token in a token database.