| CPC H04L 9/3231 (2013.01) [G06F 21/32 (2013.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06F 2221/2133 (2013.01)] | 20 Claims |

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1. A privacy-enabled authentication system comprising:
at least one processor operatively connected to a memory, the at least one processor configured to:
execute selection from a first machine learning (“ML”) process and a second ML process responsive to an authentication mode;
wherein the first ML process when executed by the at least one processor is configured to:
classify distance measurable encrypted feature vector inputs as part of identification or authentication using one or more first classification neural networks trained to predict matches to a plurality of identification classes for a respective distance measurable encrypted feature vector input;
wherein the second ML process when executed by the at least one processor is configured to:
accept plain text biometric or behavioral data as input to one or more generation neural networks and output respective distance measurable encrypted feature vectors;
generate an identification match based on comparing distances between distance measurable encrypted feature vectors; and
validate that identification results produced by the selected first and second ML processes are based on live submission from a live user, the validation including operations to determine liveness in multiple dimensions including at least a liveness evaluation of identification or authentication inputs of a matching type submitted to the selected first and second ML process during the identification or authentication as part of the evaluation of the multiple dimensions.
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