The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 17, 2023

Filed:

Jan. 22, 2021
Applicant:

Private Identity Llc, Potomac, MD (US);

Inventor:

Scott Edward Streit, Woodbine, MD (US);

Assignee:

Private Identity LLC, Potomac, MD (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 21/32 (2013.01); G06F 21/55 (2013.01); G06N 3/08 (2023.01); G06F 7/02 (2006.01); G06F 18/213 (2023.01); G06F 18/21 (2023.01); G06N 7/01 (2023.01); G06V 10/772 (2022.01); G06V 10/774 (2022.01); G06V 10/98 (2022.01); G06V 40/12 (2022.01); G06V 40/16 (2022.01); G06V 40/40 (2022.01);
U.S. Cl.
CPC ...
G06F 7/02 (2013.01); G06F 18/213 (2023.01); G06F 18/217 (2023.01); G06F 21/32 (2013.01); G06F 21/554 (2013.01); G06N 3/08 (2013.01); G06N 7/01 (2023.01); G06V 10/772 (2022.01); G06V 10/774 (2022.01); G06V 10/993 (2022.01); G06V 40/12 (2022.01); G06V 40/16 (2022.01); G06V 40/40 (2022.01);
Abstract

A set of measurable encrypted feature vectors can be derived from any biometric data and/or physical or logical user behavioral data, and then using an associated deep neural network ('DNN') on the output (i.e., biometric feature vector and/or behavioral feature vectors, etc.) an authentication system can determine matches or execute searches on encrypted data. Behavioral or biometric encrypted feature vectors can be stored and/or used in conjunction with respective classifications, or in subsequent comparisons without fear of compromising the original data. In various embodiments, the original behavioral and/or biometric data is discarded responsive to generating the encrypted vectors. In other embodiment, helper networks can be used to filter identification inputs to improve the accuracy of the models that use encrypted inputs for classification.


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