Using physiological cues to measure data sensitivity and implement security on a user device
Using physiological cues to measure data sensitivity and implement security on a user device. The method may include obtaining data associated with a first physiological state of a user engaged in a first activity on a user device, obtaining data associated with a second physiological state of the user engaged in a second activity on the user device, where the second activity is determined to be more sensitive to the user than the first activity, and where the second physiological state indicates the user's emotional response to the second activity, and implementing a security action on the user device based on the second physiological state of the user engaged in the second activity.
1. A computer-implemented method for using physiological cues to measure data sensitivity and implement security on a user device, at least a portion of the method being performed by a computer device comprising one or more processors, the method comprising:
obtaining data associated with a first physiological state of a user while the user is engaged in a first activity on a user device, wherein the first physiological state of the user is based, at least in part, on the first activity on the user device and the first activity on the user device is a non-sensitive activity that the user deems safe;
obtaining data associated with a second physiological state of the user while the user is engaged in a second activity on the user device;
comparing the first physiological state of the user with the second physiological state of the user to identify a change in the user's physiological state while the user is engaged in the second activity;
determining, based on the change in the user's physiological state while the user is engaged in the second activity, that the second activity is more sensitive to the user than the first activity; and
implementing a security action on the user device based on the determination that the second activity is more sensitive to the user than the first activity.
2. The computer-implemented method of claim 1 , further comprising:
training a machine learning model on the data obtained while the user is engaged in the first activity to determine a baseline physiological state of the user.
3. The computer-implemented method of claim 1 , further comprising:
training a machine learning model on the data obtained while the user is engaged in the second activity to determine the user's emotional response to the second activity.
4. The computer-implemented method of claim 1 , wherein the obtaining of the data associated with the first or second physiological state further comprises:
obtaining the data by way of: a sensor in electronic communication with the user device, a camera in electronic communication with the user device, or a microphone in electronic communication with the user device, or a combination thereof.
5. The computer-implemented method of claim 1 , wherein the obtaining of the data associated with the second physiological state of the user while the user is engaged in the second activity further comprises:
obtaining the data while the user is engaged in the second activity on the user device that the user deems private.
6. The computer-implemented method of claim 1 , wherein the obtaining of the data associated with the first physiological state of the user further comprises:
obtaining the user's: default heart rate, blood pressure, facial expressions, gait, pupil size, skin moisture, body temperature, voice pitch, voice speed, voice volume, or body movements, or a combination thereof.
7. The computer-implemented method of claim 6 , wherein the comparing of the first physiological state of the user with the second physiological state of the user to identify a change in the user's physiological state while the user is engaged in the second activity further comprises:
determining a change from the user's: default heart rate, blood pressure, facial expressions, gait, pupil size, skin moisture, body temperature, voice pitch, voice speed, voice volume, or body movements, or a combination thereof.
8. The computer-implemented method of claim 1 , wherein the implementing of the security action on the user device further comprises:
dimming a brightness setting of a display of the user device, blurring a portion of the display of the user device, adjusting a volume of the user device, hiding a portion of the display of the user device, or adjusting a font of characters displayed on the user device, or a combination thereof.
9. The computer-implemented method of claim 1 , further comprising:
removing the security action from the user device.
10. The computer-implemented method of claim 9 , wherein the removing of the security action from the user device further comprises:
removing the security action from the user device after expiration of a pre-determined time period for implementation of the security action.
11. The computer-implemented method of claim 9 , wherein the removing of the security action from the user device further comprises:
obtaining data associated with a third physiological state of the user, wherein the third physiological state of the user satisfies a pre-determined recovery threshold from the user's second physiological state.
12. The computer-implemented method of claim 9 , wherein the removing of the security action further from the user device comprises:
determining the user has requested the security action be removed by way of: a motion gesture, a verbal keyword, or pressing at least one button on the user device, or a combination thereof.
13. One or more non-transitory computer-readable media comprising one or more computer readable instructions that, when executed by one or more processors of a computing device, cause the computing device to perform a method for using physiological cues to measure data sensitivity and implement security on a user device, the method comprising:
obtaining data associated with a first physiological state of a user while the user is engaged in a first activity on a user device, wherein the first physiological state of the user is based, at least in part, on the first activity on the user device and the first activity on the user device is a non-sensitive activity that the user deems safe;
obtaining data associated with a second physiological state of the user while the user is engaged in a second activity on the user device;
comparing the first physiological state of the user with the second physiological state of the user to identify a change in the user's physiological state while the user is engaged in the second activity;
determining, based on the change in the user's physiological state while the user is engaged in the second activity, that the second activity is more sensitive to the user than the first activity; and
implementing a security action on the user device based on the determination that the second activity is more sensitive to the user than the first activity.
14. The non-transitory computer-readable media of claim 13 , wherein the method further comprises:
training a machine learning model on the data obtained while the user is engaged in the first activity to determine a baseline physiological state of the user.
15. The non-transitory computer-readable media of claim 13 , wherein the method further comprises:
training a machine learning model on the data obtained while the user is engaged in the second activity to determine the user's emotional response to the second activity.
16. The non-transitory computer-readable media of claim 13 , wherein the obtaining of the data associated with the second physiological state of the user further comprises:
obtaining the data by way of: a sensor in electronic communication with the user device, a camera in electronic communication with the user device, or a microphone in electronic communication with the user device, or a combination thereof.
17. The non-transitory computer-readable media of claim 13 , wherein the method further comprises:
removing the security action from the user device.
18. A system for using physiological cues to measure data sensitivity and implement security, comprising:
a processor;
a memory in electronic communication with the processor; and
instructions stored in the memory, the instructions being executable by the processor to:
obtain data associated with a first physiological state of a user while the user is engaged in a first activity on a user device, wherein the first physiological state of the user is based, at least in part, on the first activity on the user device and the first activity on the user device is a non-sensitive activity that the user deems safe;
obtain data associated with a second physiological state of the user while the user is engaged in a second activity on the user device;
compare the first physiological state of the user with the second physiological state of the user to identify a change in the user's physiological state while the user is engaged in the second activity;
determine, based on the change in the user's physiological state while the user is engaged in the second activity, that the second activity is more sensitive to the user than the first activity;
implement a security action on the user device based on the determination that the second activity is more sensitive to the user than the first activity; and
remove the security action from the user device after a pre-determined criteria is satisfied.
19. The computer-implemented method of claim 1 , wherein the first activity is deemed safe based on either a nonprivate nature of data displayed on the user device or a location of the user during the first activity.
20. The non-transitory computer-readable media of claim 13 , wherein the first activity is deemed safe based on either a nonprivate nature of data displayed on the user device or a location of the user during the first activity.