IP Library › Granted Patent US 12,047,773
Granted Patent B2
US 12,047,773 · App. 17/666,363 · Granted Jul 23, 2024

System and method for implicit authentication

Inventors: Deepak Chandra Dutt (Ottawa, CA); Anil Buntwal Somayaji (Ottawa, CA); Michael John Kendal Bingham (Ottawa, CA)
Assignee: Zighra Inc.
H04W12/06G06F1/1694G06F3/017G06F3/04883G06F21/316G06F21/32H04L63/0861H04W12/12H04W12/126G06F2221/2101G06N5/01G06N20/00G06N20/10H04W12/68
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,047,773
App. No.
17/666,363
Granted
Jul 23, 2024
Kind
B2
Abstract

A system for implicit authentication for a mobile device associated with a user, wherein the implicit authentication is behavioral, biometric and task-based and includes at least one authentication task selected so as to leverage the user's muscle memory. The mobile device comprises a touchscreen; a transaction authentication information unit; one or more sensors coupled to the transaction authentication information unit; and an anomaly detector coupled to the transaction authentication information unit. The sensors comprise one or more touchscreen sensors coupled to the touchscreen, an accelerometer, and a gyroscope, and are used to obtain and transmit one or more sets of data to the transaction authentication information unit. The sets of data are associated with one or more performances of the authentication task by the user. The anomaly detector generates an authentication model using the one or more data sets transmitted to the transaction authentication information unit.

Claims (56)

1. A computer-implemented method comprising:

obtaining sensor data, the sensor data being recorded by a mobile device while a user of the mobile device performs a selected task, the sensor data representing a motion of the mobile device in three-dimensional space while the selected task is performed;

determining a feature representation of the selected task performed by the user of the mobile device, the feature representation being based on the obtained sensor data that represents the motion of the mobile device in three-dimensional space while the selected task is performed;

analyzing the feature representation against a user model that is generated by one or more instances in which an authenticated user performed the selected task;

determining, based on analyzing the feature representation, a likelihood that the user of the mobile device is the authenticated user; and

authenticating the user of the mobile device based on the likelihood.

2. The method of claim 1 , further comprising:

determining a context of the user of the mobile device, and wherein analyzing the feature representation against the user model is adjusted for the determined context of the user.

3. The method of claim 2 , wherein determining the context is based at least in part on an environment of the mobile device.

4. The method of claim 2 , wherein determining the context is based at least in part on a location of the mobile device.

5. The method of claim 2 , further comprising determining a trust level for a transaction based on the context.

6. The method of claim 1 , wherein the sensor data is generated by one or more sensors built into a touchscreen of the mobile device.

7. The method of claim 5 , wherein the trust level is assigned based on crowdsourced data.

8. The method of claim 1 , wherein the user of the mobile device performs the selected task by swiping a touchscreen of the mobile device.

9. The method of claim 8 , wherein the feature representation includes a force applied by the user of the mobile device when swiping the touchscreen.

10. The method of claim 1 , wherein the user of the mobile device is authenticated for a transaction.

11. The method of claim 1 , wherein the method is performed on the mobile device.

12. The method of claim 1 , wherein the method is performed on one or more servers that communicate with the mobile device to obtain the sensor data.

13. The method of claim 1 , wherein determining the feature representation is performed by the mobile device, and wherein the method further comprises:

transmitting, from the mobile device, the feature representation to one or more servers; and

wherein analyzing the feature representation is performed by the one or more servers.

14. A computer system comprising:

one or more processors;

memory storing instructions;

wherein the one or more processors execute the instructions to perform operations comprising:

obtaining sensor data from a plurality of sensors of different types that are incorporated within a mobile device, the sensor data being recorded by the mobile device while a user of the mobile device performs a selected task, the sensor data representing a motion of the mobile device in three-dimensional space while the selected task is performed;

determining a feature representation of the selected task performed by the user of the mobile device, the feature representation being based on the obtained sensor data that represents the motion of the mobile device in three-dimensional space while the selected task is performed;

analyzing the feature representation against a user model that is generated by one or more instances in which an authenticated user performed the selected task;

determining, based on analyzing the feature representation, a likelihood that the user of the mobile device is the authenticated user; and

authenticating the user of the mobile device based on the likelihood.

15. The computer system of claim 14 , wherein the operations further comprise:

determining a context of the user of the mobile device, and

wherein analyzing the feature representation against the user model is adjusted for the determined context of the user.

16. The computer system of claim 14 , wherein the user of the mobile device performs the selected task by swiping a touchscreen of the mobile device.

17. The computer system of claim 16 , wherein the feature representation includes a force applied by the user of the mobile device when swiping the touchscreen.

18. The computer system of claim 14 , wherein the user of the mobile device is authenticated for a transaction.

19. The computer system of claim 14 , wherein the computer system includes the mobile device.

20. A non-transitory computer readable medium that stores instructions, that when executed by one or more processors of a computer system, cause the computer system to perform operations that include:

obtaining sensor data from a plurality of sensors of different types that are incorporated within a mobile device, the sensor data being recorded by the mobile device while a user of the mobile device performs a selected task, the sensor data representing a motion of the mobile device in three-dimensional space while the selected task is performed;

determining a feature representation of the selected task performed by the user of the mobile device, the feature representation being based on the obtained sensor data that represents the motion of the mobile device in three-dimensional space while the selected task is performed;

analyzing the feature representation against a user model that is generated by one or more instances in which an authenticated user performed the selected task;

determining, based on analyzing the feature representation, a likelihood that the user of the mobile device is the authenticated user; and

authenticating the user of the mobile device based on the likelihood.

21. The non-transitory computer readable medium of claim 20 , wherein the operations further comprise:

determining a context of the user of the mobile device, and

wherein analyzing the feature representation against the user model is adjusted for the determined context of the user.

22. The non-transitory computer readable medium of claim 21 , wherein the user of the mobile device performs the selected task by swiping a touchscreen of the mobile device.

23. The non-transitory computer readable medium of claim 22 , wherein the user of the mobile device is authenticated for a transaction.

24. A computer system comprising:

an anomaly detection module configured to analyze a feature representation of sensor data of different types recorded on a mobile device in connection with a user performing a task on the mobile device, the sensor data representing a motion of the mobile device in three-dimensional space while the task is performed on the mobile device;

wherein the anomaly detection module analyzes the feature representation against a user model that is generated by one or more instances in which an authenticated user of the mobile device performed the task; the anomaly detection module determining, based on analyzing the feature representation, a likelihood that the user of the mobile device is the authenticated user; and

a transaction authentication module configured to communicate with the anomaly detection module to authenticate the user of the mobile device based on the likelihood.

25. The computer system of claim 24 , wherein the anomaly detection module is distributed between the mobile device and one or more servers.

26. The computer system of claim 24 , wherein the anomaly detection module is implemented on a mobile device, and the transaction authentication module is implemented by one or more servers.

27. The computer system of claim 24 , wherein the transaction authentication module authenticates the user for a transaction.

28. The computer system of claim 24 , wherein the task performed by the user includes a swipe on a touchscreen of the mobile device.

Continuity (6)
Continuation 16779857 · Feb 3, 2020
Continuation 16206491 · Nov 30, 2018
Continuation 15701916 · Sep 12, 2017
Continuation In Part 14829969 · Aug 19, 2015
Provisional Application 62039019 · Aug 19, 2014
Related Publication 20220167163A1 · May 26, 2022
Cited By (2)
US 12,455,949 US 12,520,142