Systems and methods for private authentication with helper networks

A computer implemented method for privacy-enabled authentication, the method comprising:

• filtering, by at least one processor, identification information used in enrollment, identification, or authentication functions of subsequent neural networks;
• instantiating, by the at least one processor, a first pre-trained validation helper network associated with identification information of a first type comprising voice identification information, wherein the first pre-trained validation helper network is pre-trained on evaluation criteria that is independent of a subject of the identification information seeking to be enrolled, identified, or authenticated;
• evaluating, by the first pre-trained validation helper network, an unknown identification sample of the first type, responsive to input of the unknown information sample of the first type to the first pre-trained validation helper network;
• in response to determining, by the first pre-trained validation helper network, the unknown identification sample meets the evaluation criteria validating the unknown information sample for use in subsequent enrollment, identification, or authentication, or in response to determining if the unknown identification sample fails the evaluation criteria, rejecting the unknown information sample for use in subsequent enrollment, identification, or authentication;
• and
• generating, by the first pre-trained validation helper network, at least a binary evaluation of the unknown identification information sample based on the determination of the evaluation criteria, wherein generating the at least the binary evaluation includes generating an output probability by the first pre-trained validation helper network that the unknown identification information sample is valid or invalid.

An authentication system for privacy-enabled authentication, the system comprising:

• at least one processor operatively connected to a memory;
• an authentication data gateway, executed by the at least one processor, configured to filter identification information used in enrollment or identification functions of subsequent neural networks, the authentication data gateway comprising at least:
• a first pre-trained validation helper network associated with identification information of a first type comprising voice identification information, wherein the first pre-trained validation helper network is further configured to:
• evaluate identification information of the first type, wherein the first pre-trained validation helper network is trained on plaintext instances of good, bad, and spoofed identification samples, wherein good identification samples improve identification accuracy of the subsequent neural networks and bad identification samples reduce identification accuracy of the subsequent neural networks;
• responsive to input of an unknown identification sample to the first pre-trained validation helper network, identify any bad information samples, good information samples, and spoofed information samples, regardless of a subject of the unknown identification sample;
• and
• validate good information samples for use by subsequent neural network and reject bad and spoofed information samples from further processing based on at least a binary evaluation of the information sample, wherein the at least the binary evaluation includes generation of an output probability by the first pre-trained validation helper network that the unknown identification information sample is good or bad.