Methods and systems for automatically preserving a user session on a public access shared computer
A computer-implemented method may include: receiving, from at least one camera, image data associated with a first user at a public access user computing device; detecting, based on the received image data, by employing a machine learning model trained using a dataset of actions collected from a plurality of previous users, that the first user has moved away from the public access user computing device; automatically encrypting, based upon the detection, a user session associated with the first user, wherein the encrypted user session is configured to be subsequently activated by the first user; and initiating a new generic user session on the public access user computing device for a second user.
1. A computer-implemented method of activating an encrypted user session on a public access user computing device, the method comprising:
causing display, on the public access user computing device, of an option to activate the encrypted user session associated with a first user;
receiving a selection of the option to activate the encrypted user session from a requestor at the public access user computing device;
in response to receiving the selection, receiving, from at least one camera, image data of the requestor at the public access user computing device;
detecting, based on the image data, that the requestor is the first user;
retrieving, based on the detection, a session key associated with the first user;
retrieving, from a database, one or more index-difference vectors linked with the session key;
decrypting the user session associated with the first user based on calculating the user session from the retrieved one or more index-difference vectors; and
activating the user session associated with the first user on the public access user computing device.
2. The computer-implemented method of claim 1 , further comprising:
analyzing the received image data to extract facial and appearance features associated with the requestor.
3. The computer-implemented method of claim 2 , wherein retrieving, based on the detection, a session key associated with the first user includes:
retrieving the session key based on the extracted facial and appearance features.
4. The computer-implemented method of claim 1 , wherein detecting, based on the image data, that the requestor is the first user includes:
comparing the received image data of the requestor to stored image data of the first user.
5. The computer-implemented method of claim 1 , wherein the session key was generated based on previous image data associated with the first user, and wherein the session key is a hash.
6. The computer-implemented method of claim 1 , wherein the index-difference vectors were generated based on a comparison of the user session to a new generic user session.
7. The computer-implemented method of claim 2 , wherein the facial and appearance features associated with the requestor are extracted by employing at least one of a convolutional neural network (CNN) model or a long short-term memory (LSTM) recurrent neural network model on the received image data.
8. The computer-implemented method of claim 2 , wherein the extracted facial and appearance features include a size and a distance between one or more of eyes, a nose, or a mouth of the requestor.
9. A system for activating an encrypted user session on a public access user computing device, the system comprising:
a memory storing instructions; and
one or more processors operatively connected to the memory and configured to execute the instructions to perform operations including:
causing display, on the public access user computing device, of an option to activate the encrypted user session associated with a first user;
receiving a selection of the option to activate the encrypted user session from a requestor at the public access user computing device;
in response to receiving the selection, receiving, from at least one camera, image data of the requestor at the public access user computing device;
detecting, based on the image data, that the requestor is the first user;
retrieving, based on the detection, a session key associated with the first user;
retrieving, from a database, one or more index-difference vectors linked with the session key;
decrypting the user session associated with the first user based on calculating the user session from the retrieved one or more index-difference vectors; and
activating the user session associated with the first user on the public access user computing device.
10. The system of claim 9 , wherein the operations further include:
analyzing the received image data to extract facial and appearance features associated with the requestor.
11. The system of claim 10 , wherein retrieving, based on the detection, a session key associated with the first user includes:
retrieving the session key based on the extracted facial and appearance features.
12. The system of claim 9 , wherein detecting, based on the image data, that the requestor is the first user includes:
comparing the received image data of the requestor to stored image data of the first user.
13. The system of claim 9 , wherein the session key was generated based on previous image data associated with the first user, and wherein the session key is a hash.
14. The system of claim 9 , wherein the index-difference vectors were generated based on a comparison of the user session to a new generic user session.
15. The system of claim 10 , wherein the facial and appearance features associated with the requestor are extracted by employing at least one of a convolutional neural network (CNN) model or a long short-term memory (LSTM) recurrent neural network model on the received image data.
16. A computer-implemented method of activating an encrypted user session on a public access user computing device, the method comprising:
receiving, from at least one camera, image data;
detecting, based on the received image data, and by employing a machine learning model trained using a dataset of actions collected from a plurality of previous users, that a requestor has moved toward the public access user computing device;
detecting, based on the image data, that the requestor is a first user;
causing display, on the public access user computing device, of an option to activate the encrypted user session associated with the first user;
receiving a selection of the option to activate the encrypted user session from the first user at the public access user computing device;
retrieving, based on the selection, a session key associated with the first user;
retrieving, from a database, one or more index-difference vectors linked with the session key;
decrypting the user session associated with the first user based on calculating the user session from the retrieved one or more index-difference vectors; and
activating the user session associated with the first user on the public access user computing device.
17. The computer-implemented method of claim 16 , further comprising:
analyzing the received image data to extract facial and appearance features associated with the requestor.
18. The computer-implemented method of claim 17 , wherein retrieving, based on the selection, a session key associated with the first user includes:
retrieving the session key based on the extracted facial and appearance features.
19. The computer-implemented method of claim 16 , wherein detecting, based on the image data, that the requestor is the first user includes:
comparing the received image data of the requestor to stored image data of the first user.
20. The computer-implemented method of claim 16 , wherein the session key was generated based on previous image data associated with the first user, and wherein the session key is a hash.