Secure human user verification for electronic systems

Patent metadata

Field	Value
Publication number	US-2026010608-A1
Application number	US-202519268584-A
Country	US
Kind code	A1
Filing date	Jul 14, 2025
Priority date	Jul 19, 2022
Publication date	Jan 8, 2026
Grant date	—

Abstract

Systems and methods are provided for a secure human user verification procedure that involves physical manipulation of a user device with respect to its environment. A challenge prompt may be presented for a user to provide challenge response data. A subsystem of an application running on the user device may be configured (e.g., using a machine learning model) to evaluate the challenge response data and determine whether the challenge response data includes the subject of the challenge. To ensure that the user is not providing pre-existing data in response to the challenge prompt, data items associated with the challenge response data may be evaluated to validate the challenge response data as being provided by a human user rather than automatically generated.

First claim

1 . (canceled)

2 . A computer-implemented method comprising:
under control of a computing system comprising one or more processors configured to execute specific instructions:
receiving a request to perform human user verification from a requesting system;
presenting a challenge prompt instructing a user to obtain an image of a challenge subject, wherein the challenge subject is one of a plurality of potential challenge subjects;
generating a challenge response comprising image data and challenge context data;
evaluating the challenge response based on the challenge subject to generate an evaluation result indicating whether:
the image data comprises an image of the challenge subject; and
the challenge context data satisfies a response validation criterion; and

transmitting human user verification data based at least partly on the evaluation result to the requesting system.

3 . The computer-implemented method of claim 2 , further comprising transmitting an indication of a user interaction, wherein the request to perform human user verification is received in response to the indication of the user interaction.

4 . The computer-implemented method of claim 2 , wherein the request to perform human user verification comprises an identity of the challenge subject.

5 . The computer-implemented method of claim 2 , wherein the request to perform human user verification comprises the response validation criterion.

6 . The computer-implemented method of claim 2 , wherein evaluating the challenge response comprises determining, using an image recognition model, that at least a portion of the image represents the challenge subject.

7 . The computer-implemented method of claim 6 , wherein the image recognition model comprises a neural network trained to recognize the plurality of potential challenge subjects.

8 . The computer-implemented method of claim 2 , wherein the response validation criterion comprises a validation time, wherein the challenge context data comprises a time at which the image data was generated, and wherein evaluating the challenge response comprises determining whether the time at which the image data was generated is after the validation time.

9 . The computer-implemented method of claim 2 , wherein the response validation criterion comprises a validation location, wherein the challenge context data comprises a location at which the image data was generated, and wherein evaluating the challenge response comprises determining whether the location at which the image data was generated is within a threshold distance of the validation location.

10 . The computer-implemented method of claim 2 , wherein the response validation criterion comprises a device movement, wherein the challenge context data comprises a device movement information, and wherein evaluating the challenge response comprises determining whether the device movement information indicates the device was moved according to the device movement.

11 . The computer-implemented method of claim 2 , wherein the response validation criterion comprises a device identifier, wherein the challenge context data comprises a source device identifier indicating the source device used to generate the image data, and wherein evaluating the challenge response comprises determining whether the source device identifier is the device identifier.

12 . The computer-implemented method of claim 2 , further comprising:
in response to transmitting human user verification data, receiving a human user verification result; and displaying the human user verification result.

13 . The computer-implemented method of claim 2 , wherein the image data and challenge context data are not transmitted to the requesting system.

14 . The computer-implemented method of claim 2 , wherein the requesting system is at least one of: an application provider, a content provider, or an online marketplace.

15 . The computer-implemented method of claim 2 , wherein generating the challenge response comprises generating, by the computing system, at least one of: the image data or the challenge context data.

16 . A computing system comprising:
a display device; a computer-readable memory storing executable instructions; and one or more processors programmed by the executable instructions to at least:
receive a request to perform human user verification from a requesting system;
present, via the display device, a challenge prompt instructing a user to obtain an image of a challenge subject, wherein the challenge subject is one of a plurality of potential challenge subjects;
generate a challenge response comprising image data and challenge context data;
evaluate the challenge response based on the challenge subject to generate an evaluation result indicating whether:
the image data comprises an image of the challenge subject; and
the challenge context data satisfies a response validation criterion; and

transmit human user verification data based at least partly on the evaluation result to the requesting system.

17 . The computing system of claim 16 , wherein to evaluate the challenge response the executable instructions further cause the one or more processors to determine, using an image recognition model, that at least a portion of the image represents the challenge subject.

18 . The computing system of claim 17 , wherein the image recognition model comprises a neural network trained to recognize the plurality of potential challenge subjects.

19 . The computing system of claim 16 , wherein the image data and challenge context data are not transmitted to the requesting system.

20 . The computing system of claim 16 , wherein the response validation criterion comprises a validation time, wherein the challenge context data comprises a time at which the image data was generated, and wherein evaluating the challenge response comprises determining whether the time at which the image data was generated is after the validation time.

21 . The computing system of claim 16 , wherein the response validation criterion comprises a device identifier, wherein the device identifier is associated with the computing system, wherein the challenge context data comprises a source device identifier indicating the source device used to generate the image data, and wherein evaluating the challenge response comprises determining whether the source device identifier is the device identifier.

Assignees

• Tealium Inc

Inventors

• Rouse Craig P

Classifications

• G06V10/255

  Detecting or recognising potential candidate objects based on visual cues, e.g. shapes · CPC title

• H04L9/3271

  using challenge-response · CPC title

• G06F2221/2133

  Verifying human interaction, e.g., Captcha · CPC title

• G06F21/36 Primary

  by graphic or iconic representation · CPC title