Systems and methods for private authentication with helper networks
Helper neural network can play a role in augmenting authentication services that are based on neural network architectures. For example, helper networks are configured to operate as a gateway on identification information used to identify users, enroll users, and/or construct authentication models (e.g., embedding and/or prediction networks). Assuming, that both good and bad identification information samples are taken as part of identification information capture, the helper networks operate to filter out bad identification information prior to training, which prevents, for example, identification information that is valid but poorly captured from impacting identification, training, and/or prediction using various neural networks. Additionally, helper networks can also identify and prevent presentation attacks or submission of spoofed identification information as part of processing and/or validation.
1. A system for managing privacy-enabled identification or authentication, the system comprising:
at least one processor operatively connected to a memory;
an identification data gateway, executed by the at least one processor, configured to filter invalid identification information from subsequent verification, enrollment, identification, or authentication functions, the identification data gateway comprising at least:
a first pre-trained validation helper network trained on identification information of a first type, wherein the first pre-trained validation helper network is configured to:
evaluate an identification instance of the first type, responsive to input of the identification instance of the first type to the first pre-trained validation helper network, wherein the first pre-trained validation helper network is pre-trained on characteristics independent of establishing identification of a target of identification reflected in the identification instance;
responsive to a determination that the identification instance meets the evaluation criteria, validate the identification instance for use in subsequent verification, enrollment, identification, or authentication functions;
responsive to a determination that the identification instance fails the evaluation criteria, reject the unknown information instance for use in subsequent verification, enrollment, identification, or authentication functions; and
wherein the determination generates at least a binary evaluation of the identification information instance, wherein at least the binary evaluation includes: a probabilistic evaluation of the identification information instance; generation of a probability that the identification instance is valid or invalid; and evaluation of the probability against a threshold to determine that the identification instance is valid or invalid.
2. The system of claim 1 , wherein the identification data gateway is configured to filter bad audio data from use in subsequent identification of an audio target.
3. The system of claim 1 , wherein the identification data gateway is configured to accept audio data input and validate the audio input for use in identifying an audio target.
4. The system of claim 3 , wherein the at least one processor is further configured to communicate validated audio input for use in enrolling an audio target for subsequent identification.
5. The system of claim 3 , wherein the at least one processor is further configured to produce as an output from an embedding network an encrypted audio identification instance responsive to input of the identification instance of the first type to the embedding network.
6. The system of claim 5 , wherein the at least one processor is configured to associate the encrypted audio identification instance to a unique identifier for the audio target.
7. The system of claim 1 , wherein the first pre-trained validation helper network is trained on presence data, and configured to determine the presence of a target to be evaluated.
8. The system of claim 1 , wherein the target is any item or thing or entity on which identification is requested.
9. The system of claim 1 , wherein the authentication data gateway further comprises a plurality of validation helper networks each associated with a respective type of identification information, wherein each of the plurality of validation helper networks generate a binary evaluation of respective identification inputs to establish validity, wherein at least a plurality of the validation helper networks are configured to validate respective identification information independent of the target of identification.
10. A method for managing privacy-enabled identification or authentication, the method comprising:
filtering, by at least one processor, invalid identification information from subsequent verification, enrollment, identification, or authentication functions, wherein filtering includes:
instantiating a first pre-trained validation helper network trained on identification information of a first type;
evaluating, by the first pre-trained validation helper network an identification instance of the first type, responsive to input of the identification instance of the first type to the first pre-trained validation helper network, wherein the first pre-trained validation helper network is pre-trained on one or more evaluation criteria that are characteristics independent of establishing identification of a target of identification reflected in the identification instance;
determining, by the first pre-trained validation helper network that the identification instance meets or fails the evaluation criteria;
validating the identification instance for use in subsequent verification, enrollment, identification, or authentication functions responsive to determining the identification instance meets the evaluation criteria;
rejecting the unknown information instance for use in subsequent verification, enrollment, identification, or authentication functions responsive to determining the identification instance fails the evaluation criteria; and
wherein the act of determining includes generating at least a probabilistic evaluation of the identification information instance, wherein at least the probabilistic evaluation includes generation of a probability that the identification instance is valid or invalid based on evaluating the probability against a threshold for determining that the identification instance is valid or invalid.
11. The method of claim 10 , further comprising filtering bad audio data from use in subsequent identification of an audio target.
12. The method of claim 10 , further comprising accepting audio data input and validating the audio input for use in identifying an audio target.
13. The method of claim 12 , further comprising communicating validated audio input for use in enrolling an audio target for subsequent identification.
14. The method of claim 12 , further comprising producing as an output from an embedding network an encrypted audio identification instance responsive to input of the identification instance of the first type to the embedding network.
15. The method of claim 14 , further comprising associating the encrypted audio identification instance to a unique identifier for the audio target.
16. The method of claim 10 , wherein the first pre-trained validation helper network is trained on presence data, and the method further comprises determining the presence of a target to be evaluated.
17. The method of claim 10 , wherein the target is any item or thing or entity on which identification is requested.
18. The method of claim 10 , further comprising instantiating a plurality of validation helper networks each associated with a respective type of identification information, wherein each of the plurality of validation helper networks generates a probabilistic evaluation of respective identification inputs to establish validity, and the method further comprises validating respective identification information independent of the identity of the target of identification.