Systems and methods for privacy-enabled biometric processing

A privacy-enabled authentication system comprising:

• at least one processor operatively connected to a memory, the at least one processor configured to:
• execute machine learning (“ML”) functionality responsive to an authentication mode;
• based on executing a first authentication mode:
• access an identity token for an entity to be identified or authenticated, wherein the identity token is generated based, at least in part, on input of plain text biometric or behavioral data to at least a first neural network;
• classify the identity token as part of identification or authentication, including operations to predict matches using the identity token and a plurality of identification classes;
• based on a executing a second authentication mode:
• accept plain text biometric or behavioral data as input into the first neural network to output, at least in part, respective identity tokens;
• generate an identification match based, at least in part, on comparing distances between the respective identity tokens and a plurality of identification classes that are based on, at least in part, prior identity tokens generated for respective entities, to determine the match to an identity;
• and
• validate that identification results produced are based on live submission from a live entity, the validation including operations to determine liveness in multiple dimensions including at least a liveness evaluation of identification or authentication inputs submitted during the first authentication mode and the second authentication mode during the identification or authentication as part of the evaluation of the multiple dimensions.

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

• executing, by at least one processor, machine learning (“ML”) functionality responsive to an authentication mode;
• accessing, by the at least one processor, an identity token for an entity to be identified or authenticated, wherein the identity token is generated based, at least in part, on input of plain text biometric or behavioral data to at least a first neural network in response to executing a first authentication mode;
• classifying, by the at least one processor, the identity token as part of identification or authentication, including operations to predict matches using the identity token and a plurality of identification classes as part of the first authentication mode;
• accepting, by the at least one processor, plain text biometric or behavioral data as input into the first neural network to output, at least in part, respective identity tokens in response to executing a second authentication mode;
• generating, by the at least one processor, an identification match based, at least in part, on comparing distances between the respective identity tokens and a plurality of identification classes that are based on, at least in part, prior identity tokens generated for respective entities, to determine the match to an identity;
• and
• validating, by the at least one processor, identification results produced are based on live submission from a live entity, the validation including operations to determine liveness in multiple dimensions including at least a liveness evaluation of identification or authentication inputs submitted during the first authentication mode and the second authentication mode during the identification or authentication as part of the evaluation of the multiple dimensions.