IP Library Granted Patent US 11,741,263
Granted Patent B1
US 11,741,263 · App. 17/702,366 · Granted Aug 29, 2023

Systems and processes for lossy biometric representations

Inventors: Norman Hoon Thian Poh (Atlanta, GA); Gareth Neville Genner (Atlanta, GA)
Assignee: T Stamp Inc.
G06F21/6254H04L9/0643H04L9/0869H04L9/3231
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Quick Facts
Patent No.
US 11,741,263
App. No.
17/702,366
Granted
Aug 29, 2023
Kind
B1
Abstract

Systems and processes for improved processing of biometric data may include a hash controller including a processor, a server, and a registry. The hash controller can receive biometric information, such as a biometric scan, and apply an EGH transformation to convert the biometric information into an irreversible, unlinkable, and revocable EgHash. The EGH transformation can include blending biometric information with non-biometric information and permuting the biometric representation for additional security. The permuted biometric representation can be projected based on a randomly generated matrix and the output permuted to obtain an EgHash. The resultant EgHash can be lossy such that the EGH transform causes an irreversible loss of biometric information between the original biometric information and the EgHash. The EgHash can be compared and retrieved at speed and scale by the processor to support operations including, but not limited to, verification, identification, and database deduplication.

Claims (52)

1. A process comprising:

obtaining a biometric representation of a subject, wherein the biometric representation was encoded from a biometric sample via a neural network;

concatenating the biometric representation with a key to generate a concatenated biometric representation;

multiplying the concatenated biometric representation by a pseudorandom matrix to generate an anonymized vector representation;

receiving a second biometric representation associated with the subject;

generating a second anonymized vector representation based on the second biometric representation;

performing a 1:1 comparison between the anonymized vector representation and the second anonymized vector representation to generate a similarity score;

determining that the similarity score satisfies a similarity threshold; and

in response to determining the similarity score satisfies the similarity threshold, confirming a positive verification of an identity of the subject.

2. The process of claim 1 , wherein a vector dimension of the anonymized vector representation is less than a vector dimension of the concatenated biometric representation.

3. The process of claim 1 , wherein a vector dimension of the anonymized vector representation is equal to a vector dimension of the concatenated biometric representation.

4. The process of claim 1 , further comprising:

generating a random seed; and

prior to multiplying the concatenated biometric representation, generating the pseudorandom matrix based on the random seed.

5. The process of claim 4 , wherein the random seed is generated based on a second key.

6. The process of claim 5 , wherein the second key is a unique key received from a user.

7. The process of claim 5 , wherein the second key is a common key associated with a particular organization and is received with the biometric representation.

8. A system comprising:

at least one processor; and

a non-transitory, machine-readable memory device comprising instructions stored thereon that, when executed by the at least one processor, cause the at least one processor to:

obtain a biometric representation of a subject, wherein the biometric representation was encoded from a biometric sample via a neural network;

concatenate the biometric representation with a key to generate a concatenated biometric representation;

multiply the concatenated biometric representation by a pseudorandom matrix to generate an anonymized vector representation;

receive a second biometric representation associated with the subject;

generate a second anonymized vector representation based on the second biometric representation;

perform a 1:1 comparison between the anonymized vector representation and the second anonymized vector representation to generate a similarity score;

determine that the similarity score satisfies a similarity threshold; and

in response to determining the similarity score satisfies the similarity threshold, confirm a positive verification of an identity of the subject.

9. The system of claim 8 , wherein a vector dimension of the anonymized vector representation is less than a vector dimension of the biometric representation.

10. The system of claim 8 , wherein a vector dimension of the anonymized vector representation is equal to a vector dimension of the biometric representation.

11. The system of claim 8 , further comprising:

generating a random seed; and

prior to multiplying the concatenated biometric representation, generating the pseudorandom matrix based on the random seed.

12. The system of claim 11 , wherein the random seed is generated based on a second key.

13. The system of claim 12 , wherein the second key is a unique key received from a user.

14. The system of claim 12 , wherein the second key is a common key associated with a particular organization and is received with the biometric representation.

15. A non-transitory, computer-readable medium comprising instructions that, when executed by a computer, cause the computer to:

obtain a biometric representation of a subject, wherein the biometric representation was encoded from a biometric sample via a neural network;

concatenate the biometric representation with a key to generate a concatenated biometric representation;

multiply the concatenated biometric representation by a pseudorandom matrix to generate an anonymized vector representation;

receive a second biometric representation associated with the subject;

generate a second anonymized vector representation based on the second biometric representation;

perform a 1:1 comparison between the anonymized vector representation and the second anonymized vector representation to generate a similarity score;

determine that the similarity score satisfies a similarity threshold; and

in response to determining the similarity score satisfies the similarity threshold, confirm a positive verification of an identity of the subject.

16. The non-transitory, computer-readable medium of claim 15 , wherein a vector dimension of the anonymized vector representation is less than a vector dimension of the biometric representation.

17. The non-transitory, computer-readable medium of claim 15 , wherein a vector dimension of the anonymized vector representation is equal to a vector dimension of the concatenated biometric representation.

18. The non-transitory, computer-readable medium of claim 15 , wherein the instructions, when executed by the computer, cause the computer to:

generate a random seed; and

prior to multiplying the concatenated biometric representation, generate the pseudorandom matrix based on the random seed.

19. The non-transitory, computer-readable medium of claim 18 , wherein the random seed is generated based on a second key.

20. The non-transitory, computer-readable medium of claim 19 , wherein the second key is a unique key received from a user.

Assignments (5)
RELEASE OF SECURITY INTEREST Recorded Oct 6, 2025
From: STREETERVILLE CAPITAL, LLC
To: T STAMP INC.
Reel/Frame 073010/0488 →
SECURITY INTEREST Recorded Jul 2, 2025
From: T STAMP INC.
To: STREETERVILLE CAPITAL, LLC
Reel/Frame 071800/0427 →
RELEASE OF SECURITY INTEREST Recorded Jan 17, 2025
From: SENTILINK CORP.
To: T STAMP INC.
Reel/Frame 069918/0538 →
SECURITY INTEREST Recorded Nov 21, 2024
From: T STAMP INC.
To: SENTILINK CORP.
Reel/Frame 069362/0398 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 31, 2022
From: POH, NORMAN HOON THIAN; GENNER, GARETH NEVILLE
To: T STAMP INC.
Reel/Frame 059458/0045 →
Continuity (2)
Continuation 16841269 · Apr 6, 2020
Provisional Application 62829825 · Apr 5, 2019