Biometric identification using homomorphic primary matching with failover non-encrypted exception handling
AssigneeThe Government of the United States of America, as represented by the Secretary of Homeland Security
InventorArun Vemury
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Abstract
Systems and methods for providing exception failover augmented, homomorphic encrypted (HE) distributing, end-to-endpoint persistent encryption, and distributed HE domain non-decrypting, privacy-protective biometric processing are provided. Some configurations may include generating HE biometric feature data, based on homomorphic encrypting the biometric feature data. Some configurations determine an exception status of the HE biometric feature data between exception and non-exception. Systems and methods may include performing a HE domain, non-decrypting biometric classifying of the HE biometric feature data.
Claims21
A method comprising:
- generating and distributing by a system controller a HE encrypted reference biometric FV table for a third-party computer resource and a controller-generated fail-over exception table for a biometric capture and HE encrypted distribution unit;
- generating a reference biometric HE vector table for biometric information;
- generating a biometric reference gallery of integer N reference images, RG(i), i=1, N;
- include initializing an “i” index to integer 1;
- and
- computing a feature vector FV(RG(i)) from the RG(i), at i equal to integer 1.
A method for secure privacy-protective HE distribution and persistent encryption HE secured, non-decrypting distributed biometric processing, with a priori distribution of exceptions, for local cleartext failover comprising:
- providing a third-party computer resource;
- a biometric capture, HE encrypted distribution station;
- a biometric processing exception detection and failover logic comprising a central HE vector exception table;
- a HE{FV} validity logic;
- a FO VF-ID logic, a HE FV table;
- a reference HE FV table, for HE{FV(RG(j))}, j=1, NC;
- a FV(RG(i)) logic;
- a HE{FV(RG(i))} logic;
- and a HE vector table collision detect, update logic;
- a HE domain classifier configuring logic generating a cleartext biometric reference gallery;
- the cleartext biometric reference gallery comprising HE encryption of distinguishing information regarding M biometric reference images;
- setting an index i to 1;
- retrieving the RG(1) biometric reference image from the cleartext biometric reference gallery;
- feeding RG(1) to obtain the HE encrypted FV for RG(1);
- the HE vector collision detect logic receiving HE{FV(RG(1))} and checking to determine if a reference HE FV table already includes a HE vector of identical value;
- loading HE{FV(RG(1))} into the reference HE FV table;
- and
- constructing the reference HE FV table for performing another iteration.
A method of distributed privacy protective, HE persistent encryption locked, non-decrypting biometric identification and verification processing, with exception failover backup for exception failover augmented, homomorphic encrypted (HE) distributing, end-to-endpoint persistent encryption, and distributed HE domain non-decrypting, privacy-protective biometric processing of a current user K comprising:
- receiving an HE encrypted reference gallery of N HE encrypted reference files from the current user K;
- each of the N HE encrypted reference files corresponding to a verified reference identity;
- receiving HE encrypted feature vectors representing captured facial image information from a biometric capture EP HE ECDS unit in response to user interactions with the biometric capture EP HE ECDS unit;
- performing HE domain, non-decrypting N+1 class classification of the HE encrypted feature vectors, using a vector similarity algorithm;
- detecting an exception;
- and
- providing failover processing by the biometric capture, EP HE ECDS unit in response to detecting the exception.
Dependencies are inferred from the claim text.