Verification request authentication machine
A device authenticates a request to verify a user. The device accesses a face image that depicts a face of the person and includes a characteristic noise pattern inserted by a camera of the device. The device also accesses a geolocation at which the device captured the face image and inputs the face image and the geolocation into an artificial intelligence engine that outputs a face score, a device score, and a location score. The device next submits the request with the scores to a server machine and obtains an authentication score from the server machine. The device then presents an indication that the request to verify the person is authentic based on a comparison of the obtained authentication score to a threshold authentication score.
1. A method comprising:
causing, by one or more processors, an artificial intelligence engine to process an image that depicts a face of a user and includes a noise pattern of a camera that captured the image, the artificial intelligence engine generating a face score based on the image and generating a camera score based on the noise pattern;
obtaining, by the one or more processors, an authentication score based on the face score and the camera score; and
causing, by the one or more processors, presentation of an indication that a request that corresponds to the user is authentic based on the authentication score.
2. The method of claim 1 , further comprising:
causing the artificial intelligence engine to process location data that indicates a location at which the camera captured the image; and wherein:
the artificial intelligence engine is trained to generate a location score based on the indicated location at which the camera captured the image; and
the obtaining of the authentication score is based on the location score, the face score, and the camera score.
3. The method of claim 2 , further comprising:
accessing the image from the camera that captured the image; and
in response to the accessing of the image from the camera, accessing the location data from a location sensor communicatively coupled to the camera.
4. The method of claim 2 , further comprising:
accessing the image from a device that includes the camera that captured the image; and
in response to the accessing of the image from the device, accessing the location data from metadata of the image.
5. The method of claim 2 , further comprising:
accessing accelerometer data that indicates a movement of the camera during capture of the image; and wherein:
the artificial intelligence engine is trained to generate the camera score based on the accelerometer data.
6. The method of claim 2 , wherein:
the artificial intelligence engine is trained to generate the location score based on a background analysis of the image.
7. The method of claim 2 , wherein:
the artificial intelligence engine is trained to generate the location score based on a metadata analysis of the image.
8. The method of claim 1 , wherein:
the noise pattern of the camera indicates a set of one or more manufacturing deviations that occurred during manufacture of the camera.
9. The method of claim 1 , wherein:
the artificial intelligence engine trained to generate the face score and the camera score includes one or more of a deep neural network, a convolutional neural network, or a recurrent neural network.
10. The method of claim 1 , wherein:
the obtaining of the authentication score includes causing the face score and the camera score to be inputted into a neural network and obtaining the authentication score as output therefrom.
11. The method of claim 1 , wherein:
the artificial intelligence engine is trained to generate the face score based on a liveness analysis of the image.
12. A non-transitory machine-readable storage medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform operations comprising:
causing an artificial intelligence engine to process an image that depicts a face of a user and includes a noise pattern of a camera that captured the image, the artificial intelligence engine generating a face score based on the image and generating a camera score based on the noise pattern;
obtaining an authentication score based on the face score and the camera score; and
causing presentation of an indication that a request that corresponds to the user is authentic based on the authentication score.
13. The non-transitory machine-readable storage medium of claim 12 , wherein the operations further comprise:
causing the artificial intelligence engine to process location data that indicates a location at which the camera captured the image; and wherein:
the artificial intelligence engine is trained to generate a location score based on the indicated location at which the camera captured the image; and
the obtaining of the authentication score is based on the location score, the face score, and the camera score.
14. The non-transitory machine-readable storage medium of claim 13 , wherein the operations further comprise:
accessing accelerometer data that indicates a movement of the camera during capture of the image; and wherein:
the artificial intelligence engine is trained to generate the camera score based on the accelerometer data.
15. The non-transitory machine-readable storage medium of claim 12 , wherein:
the noise pattern of the camera indicates a set of one or more manufacturing deviations that occurred during manufacture of the camera.
16. A system comprising:
one or more processors; and
a memory storing instructions that, when executed by at least one processor among the one or more processors, cause the system to perform operations comprising:
causing an artificial intelligence engine to process an image that depicts a face of a user and includes a noise pattern of a camera that captured the image, the artificial intelligence engine generating a face score based on the image and generating a camera score based on the noise pattern;
obtaining an authentication score based on the face score and the camera score; and
causing presentation of an indication that a request that corresponds to the user is authentic based on the authentication score.
17. The system of claim 16 , wherein the operations further comprise:
causing the artificial intelligence engine to process location data that indicates a location at which the camera captured the image; and wherein:
the artificial intelligence engine is trained to generate a location score based on the indicated location at which the camera captured the image; and
the obtaining of the authentication score is based on the location score, the face score, and the camera score.
18. The system of claim 17 , wherein the operations further comprise:
accessing accelerometer data that indicates a movement of the camera during capture of the image; and wherein:
the artificial intelligence engine is trained to generate the camera score based on the accelerometer data.
19. The system of claim 17 , wherein:
the artificial intelligence engine is trained to generate the location score based on a background analysis of the image.
20. The system of claim 16 , wherein:
the noise pattern of the camera indicates a set of one or more manufacturing deviations that occurred during manufacture of the camera.