Active locking mechanism using machine learning
Methods and systems disclosed herein describe using machine learning to lock and unlock a device. Machine learning may be trained to recognize one or more features. Once the device has been trained to recognize one or more features, a user may define an unlock condition for the device using the one or more trained features. After defining the unlock condition, the device may be locked by verifying the one or more features that the user defined as the unlock condition using machine learning. When verification is successful, the device may be unlocked and the user allowed to access the device.
1. A computing device comprising:
one or more processors; and
memory storing instructions that, when executed by the one or more processors, cause the computing device to:
receive a request to unlock a portion of the computing device's capabilities;
receive, via one or more inputs of the computing device, a first authentication parameter and a second authentication parameter, wherein the second authentication parameter comprises a background element;
determine, using a first machine learning model trained to identify a first baseline parameter associated with a lock condition, that the first authentication parameter matches the first baseline parameter;
determine, using the first machine learning model, a physical state of a user requesting unlocking of the portion of the computing device's capabilities;
determine, using a second machine learning model trained to identify a second baseline parameter associated with the lock condition, that the second authentication parameter matches the second baseline parameter;
determine, based on the physical state of the user, based on the first authentication parameter matching the first baseline parameter, and based on the second authentication parameter matching the second baseline parameter, that an unlock condition has been satisfied; and
unlock, based on a determination that the unlock condition has been satisfied, the portion of the computing device's capabilities.
2. The computing device of claim 1 , wherein the instructions, when executed by the one or more processors, cause the computing device to:
decrypt a storage medium associated with the computing device.
3. The computing device of claim 1 , wherein the first authentication parameter comprises a biometric identifier.
4. The computing device of claim 3 , wherein the background element comprises at least one of:
a background associated with a location;
a background image;
an ambient sound; or
an orientation of the computing device.
5. The computing device of claim 1 , wherein the instructions, when executed by the one or more processors, cause the computing device to:
receive a lock command, wherein the lock command comprises a definition of the unlock condition.
6. The computing device of claim 1 , wherein the instructions, when executed by the one or more processors, cause the computing device to:
determine that a first geographic location of the computing device corresponds to a second geographic location defined in the unlock condition.
7. The computing device of claim 1 , wherein the instructions, when executed by the one or more processors, cause the computing device to determine that the unlock condition has been satisfied by determining that a current time corresponds to a time range defined in the unlock condition.
8. The computing device of claim 1 , wherein the instructions, when executed by the one or more processors, cause the computing device to determine that the physical state of the user is at least one or more of:
not being coerced;
not in poor health; or
not under duress.
9. A non-transitory computer-readable medium storing instructions that, when executed, configure a computing device to:
receive a request to unlock a portion of the computing device's capabilities;
receive, via one or more inputs of the computing device, a first authentication parameter and a second authentication parameter, wherein the second authentication parameter comprises a background element;
determine, using a first machine learning model trained to identify a first baseline parameter associated with a lock condition, that the first authentication parameter matches the first baseline parameter;
determine, using the first machine learning model, a physical state of a user requesting unlocking of the portion of the computing device's capabilities;
determine, using a second machine learning model trained to identify a second baseline parameter associated with the lock condition, that the second authentication parameter matches the second baseline parameter;
determine, based on the physical state of the user, based on the first authentication parameter matching the first baseline parameter, and based on the second authentication parameter matching the second baseline parameter, that an unlock condition has been satisfied; and
unlock, based on a determination that the unlock condition has been satisfied, the portion of the computing device's capabilities.
10. The non-transitory computer-readable medium of claim 9 , wherein the instructions, when executed, configure the computing device to:
decrypt a storage medium associated with the computing device.
11. The non-transitory computer-readable medium of claim 9 , wherein the first authentication parameter comprises a biometric identifier.
12. The non-transitory computer-readable medium of claim 11 , wherein the background element comprises at least one of:
a background associated with a location;
a background image;
an ambient sound; or
an orientation of the computing device.
13. The non-transitory computer-readable medium of claim 9 , wherein the instructions, when executed, configure the computing device to:
receive a lock command, wherein the lock command comprises a definition of the unlock condition.
14. The non-transitory computer-readable medium of claim 9 , wherein the instructions, when executed, configure the computing device to:
determine that a first geographic location of the computing device corresponds to a second geographic location defined in the unlock condition.
15. The non-transitory computer-readable medium of claim 9 , wherein the instructions, when executed, configure the computing device to determine that the unlock condition has been satisfied by determining that a current time corresponds to a time range defined in the unlock condition.
16. The computing device of claim 9 , wherein the instructions, when executed by the one or more processors, cause the computing device to determine that the physical state of the user is at least one or more of:
not being coerced;
not in poor health; or
not under duress.
17. A computing device comprising:
one or more processors; and
memory storing instructions that, when executed by the one or more processors, cause the computing device to:
define a plurality of features for unlocking a portion of the computing device's capabilities;
train a machine learning model to recognize a first feature and a second feature;
define, based on training the machine learning model to recognize the first feature and the second feature, an unlock condition, wherein the unlock condition comprises authenticating the first feature and the second feature; and
lock, based on defining the unlock condition, the portion of the computing device's capabilities.
18. The computing device of claim 17 , wherein the instructions, when executed by the one or more processors, cause the computing device to encrypt a storage medium associated with the computing device.
19. The computing device of claim 17 , wherein the first feature comprises a biometric identifier of a user.
20. The computing device of claim 19 , wherein the second feature comprises at least one of:
a background associated with a location;
a background image;
an ambient sound; or
an orientation of the computing device.
21. The computing device of claim 17 , wherein the defining the unlock condition comprises at least one of:
defining a geographic location where the computing device may be unlocked; or
defining a time range for when the computing device may be unlocked.
22. A non-transitory computer-readable medium storing instructions that, when executed, configure a computing device to:
define a plurality of features for unlocking a portion of the computing device's capabilities;
train a machine learning model to recognize a first feature and a second feature;
define, based on training the machine learning model to recognize the first feature and the second feature, an unlock condition, wherein the unlock condition comprises authenticating the first feature and the second feature; and
lock, based on defining the unlock condition, the portion of the computing device's capabilities.
23. The non-transitory computer-readable medium of claim 22 , wherein the instructions, when executed, configure the computing device to encrypt a storage medium associated with the computing device.
24. The non-transitory computer-readable medium of claim 22 , wherein the first feature comprises a biometric identifier of a user.
25. The non-transitory computer-readable medium of claim 24 , wherein the second feature comprises at least one of:
a background associated with a location;
a background image;
an ambient sound; or
an orientation of the computing device.
26. The non-transitory computer-readable medium of claim 22 , wherein the defining the unlock condition comprises at least one of:
defining a geographic location where the computing device may be unlocked; or defining a time range for when the computing device may be unlocked.