CN-121986337-A - Authentication services and techniques

Abstract

Authentication services and techniques are described. In one or more implementations, an authentication service is used to control resource access based on authentication. In a first example, the authentication service compares actions (e.g., head movements, gestures, etc.) depicted in the authentication input data as being performed by the user to determine whether the actions correspond to actions specified by the selected authentication prompt. In a second example, the authentication service determines a likelihood of verifying whether a user depicted in the input data corresponds to a human by using a machine learning model. In a third example, a depiction of a user's face captured by verification input data is compared to a digital image of the user maintained by a verification system. Resource access is controlled by an authentication service.

Inventors

• XU YONGSONG
• ZHU JIAN
• TAO FUJUN
• WANG XIAOTONG

Assignees

• 电子湾有限公司

Dates

Publication Date

20260505

Application Date

20231123

Claims (20)

1. 1. A method, comprising: Selecting, by the processing device, a validation hint from a plurality of validation hints; receiving, by the processing device, authentication input data in response to the authentication prompt; Determining, by the processing device, whether the validation input data is valid, the determining comprising: Confirming whether or not the action depicted in the authentication input data as being performed by the user corresponds to the action specified by the selected authentication prompt, and Confirming a possibility that a user depicted in the verification input data corresponds to a human being using a machine learning model, and Controlling, by the processing device, resource access based on a result of the determining.
2. 2. The method of claim 1, wherein the verification prompt specifies a motion prompt to be performed using motion of the user's head.
3. 3. The method of claim 1, wherein the verification prompt specifies a motion prompt to be performed using motion of the user's hand.
4. 4. A method according to claim 3, wherein the motion of the hand involves a gesture.
5. 5. The method of claim 1, wherein the verification prompt is configured for display in a user interface at a client device associated with the user.
6. 6. The method of claim 5, wherein the verification prompt includes a visual guide configured to guide alignment of the depiction of the user in the digital image captured by the image capture device of the client device.
7. 7. The method of claim 5, wherein the verification prompt includes a visual guide configured to provide real-time feedback in the user interface based on the captured one or more digital images of the user.
8. 8. The method of claim 5, wherein the verification prompt includes an output of a representation of a timer indicating an amount of time available to capture a digital image of the user when performing the action.
9. 9. The method of claim 5, wherein the verification prompt includes a graphical depiction of the action to be performed.
10. 10. The method of claim 9, wherein the graphical depiction depicts a hand as a graphical representation of a gesture to be performed as part of the action.
11. 11. The method of claim 5, wherein the verification prompt includes a visual guide configured to guide alignment of a depiction of the user's hand in a digital image captured by an image capture device of the client device.
12. 12. The method of claim 1, wherein the determining comprises comparing a depiction of the user's face captured by the verification input data with a digital image of the user obtained through a verification system via a network.
13. 13. The method of claim 12, wherein the digital image is included as part of a passport or a driver's license.
14. 14. The method of claim 1, wherein the machine learning model is trained using positive sample training data with real user depictions and negative sample training data with false user depictions.
15. 15. The method of claim 14, wherein the false user depiction is generated using generative artificial intelligence implemented using machine learning.
16. 16. One or more computer-readable storage media storing instructions that, in response to execution by a processing device, cause the processing device to perform operations comprising: Selecting a verification hint from a plurality of verification hints; receiving authentication input data in response to the authentication prompt; controlling resource access by determining whether the validation input data is valid, the determining comprising: Confirming whether or not the action depicted in the authentication input data as being performed by the user corresponds to the action specified by the selected authentication prompt, and A machine learning model is used to confirm a likelihood that the user depicted in the verification input data corresponds to a human.
17. 17. The one or more computer-readable storage media of claim 16, wherein the action specifies a motion of the user's hand or the user's head.
18. 18. A computing device, comprising: An image capturing device; Processing apparatus, and A computer-readable storage medium storing instructions that, in response to execution by the processing device, cause the processing device to perform operations comprising: Displaying a verification prompt in a user interface, the verification prompt specifying an action to be performed by a user; Displaying in real time a plurality of digital images captured by the image capture device in the user interface, the plurality of digital images depicting the user, and Access to a resource is accepted in response to a determination being made that the plurality of digital images depicts the user as performing the action.
19. 19. The computing device of claim 18, wherein the action specifies a motion of the user's hand or the user's head.
20. 20. The computing device of claim 18, wherein the determining comprises comparing a depiction in a digital image of the user's face captured by the image capture device at an unspecified point in time in the user interface with a digital image obtained from a verification system.

Description

Authentication services and techniques Background The computing device utilizes authentication of the user identity as a basis to control access to various resources, whether for access to resources implemented locally at the computing device and/or remotely by a service provider system as a digital service. Various methods and techniques have been developed to enable authentication, e.g., user passwords, facial recognition, etc. However, these techniques are continually challenged by malicious parties, such as by using photographs to detect facial recognition techniques, hacking camera feeds, employing artificial intelligence, and so forth. Thus, conventional methods for authentication may not be able to achieve their intended purpose, exposing these resources to access by malicious parties. Disclosure of Invention Authentication services and techniques are described. In one or more implementations, an authentication service is used to control resource access based on authentication. In a first example, the authentication service compares actions (e.g., head movements, gestures, etc.) depicted in the authentication input data as being performed by the user to determine whether the actions correspond to actions specified by the selected authentication prompt. In a second example, the authentication service determines a likelihood of verifying whether a user depicted in the input data corresponds to a human by using a machine learning model. In a third example, a depiction of a user's face captured by the verification input data is compared to a digital image of the user maintained by the verification system. Based on the result of the determination, resource access is controlled by the authentication service. This summary presents in simplified form a series of concepts that are further described in the detailed description below. Accordingly, this summary is not intended to identify essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter. Drawings The specific embodiments are described with reference to the accompanying drawings. The entities represented in the figures indicate one or more entities, and thus singular or plural forms of entities may be referred to interchangeably in the discussion. FIG. 1 is an illustration of an environment in an example implementation that is operable with the authentication techniques described herein. FIG. 2 depicts in more detail a system in an example implementation showing training of the machine learning model of FIG. 1. FIG. 3 depicts an example implementation of pseudo code that may be used to implement training of a machine learning model. FIG. 4 depicts a system in an example implementation in which a prompt module outputs a prompt and an action recognition module validates authentication input data in response to the prompt for authentication by an authentication service. FIG. 5 depicts a system in an example implementation in which a hint module and an action recognition module utilize motion as part of an action being performed for authentication through an authentication service. FIG. 6 depicts an example implementation showing the output of a validation hint with a motion hint and the generation of a motion response as part of validation input data. FIG. 7 depicts an example implementation of pseudo code that may be used to implement action recognition by the action recognition module. FIG. 8 depicts a system in an example implementation in which a prompt module and an action recognition module utilize gestures as part of authentication through an authentication service. FIG. 9 depicts an example implementation showing the output of a verification prompt with a gesture prompt and the generation of a gesture response as part of verification input data. FIGS. 10 and 11 depict example implementations of pseudo code that may be used to implement gesture recognition by the action recognition module. FIG. 12 depicts an example implementation showing operation of the ID verification module of FIG. 1 in more detail. Fig. 13 depicts an additional example implementation that illustrates using authentication as part of controlling access to a resource configured as an electronic message. Figure 14 is a flow chart depicting a procedure in an example implementation that is stepwise in an operation that is executable for accomplishing a result of authentication. Fig. 15 illustrates an example system including various components of example devices that can be implemented as any type of computing device described with reference to previous figures and/or utilized to implement embodiments of the techniques described herein. Detailed Description SUMMARY The computing device utilizes authentication of the user to control access to various resources, such as obtaining local access to the computing device, remotely accessing digital services via a network, proving that a human is attempting