IP Library › Granted Patent US 11,704,439
Granted Patent B2
US 11,704,439 · App. 16/890,991 · Granted Jul 18, 2023

Systems and methods for managing privacy policies using machine learning

Inventors: Michelle Bonat (New York, NY); Tuan Dao (Richardson, TX); Roderic Bachelor (San Carlos, CA); Jeremy F. Bennett (San Carlos, CA); Ralph Darmo (West Chester, CA); Andrew Grignon (Half Moon Bay, CA); Kathleen Moynahan (Oakland, CA)
Assignee: JPMORGAN CHASE BANK, N.A.
G06F21/6263G06F16/955G06F21/602G06F21/6254G06F40/279G06N20/00H04L9/3213H04L63/1425H04L63/20H04W12/02G01S19/42G06F2221/2149H04L61/5007H04L67/02
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Quick Facts
Patent No.
US 11,704,439
App. No.
16/890,991
Granted
Jul 18, 2023
Kind
B2
Abstract

Systems, methods, and devices for managing privacy policies are disclosed. In one embodiment, a method for management of a user's privacy preferences may include: identifying a computer application installed on a user electronic device, or a website accessed using a browser executed by the user electronic device; retrieving a privacy policy document analysis for a privacy policy document associated with the computer application or the website, the privacy policy document analysis comprising a valuation of a plurality of privacy policy segments within the privacy policy document; receiving a privacy preference analysis for the user, the privacy preference analysis comprising a valuation of a plurality of privacy preferences for the user; identifying a recommended action in response to the valuation of one of the privacy policy segments being outside the scope of the valuation of one of the plurality of privacy preferences; and executing the recommended action.

Claims (35)

1. A method for management of a user's privacy preferences, comprising:

in an information processing apparatus comprising at least one computer processor:

identifying a computer application installed on a user electronic device, or a website accessed using a browser executed by the user electronic device by examining network traffic to and from the user electronic device via a network monitor separate from the user electronic device;

retrieving a privacy policy document analysis for a privacy policy document associated with the computer application or the website, the privacy policy document analysis comprising a valuation of a plurality of privacy policy segments within the privacy policy document;

receiving a privacy preference analysis for the user, the privacy preference analysis comprising a valuation of a plurality of privacy preferences for the user;

identifying a recommended action in response to the valuation of one of the privacy policy segments being outside the scope of the valuation of one of the plurality of privacy preferences; and

executing the recommended action.

2. The method of claim 1 , wherein the privacy policy document analysis is a result of natural language processing of the privacy policy document.

3. The method of claim 1 , wherein each privacy policy segment comprises a privacy category, a privacy sub-category, and a privacy sub-category classification.

4. The method of claim 3 , wherein the valuation of the privacy policy segment is based on at least one of the privacy sub-category and the privacy sub-category classification for the privacy policy segment.

5. The method of claim 1 , wherein the valuation of the privacy policy segment comprises a numeric score, a letter grade, or a color code.

6. The method of claim 1 , further comprising:

modifying the valuation of the privacy policy segment based on an actual implementation of the privacy policy segment.

7. The method of claim 1 , wherein the valuation of a plurality of privacy preference is based on monitored user behavior.

8. The method of claim 1 , wherein the recommended action is to change the valuation of the user privacy preference.

9. The method of claim 1 , wherein the recommended action is based on an action taken by a second user.

10. The method of claim 1 , wherein the recommended action is based on news related to an entity associated with the computer application or website.

11. The method of claim 1 , wherein the recommendation is to restrict use of the computer application or website.

12. The method of claim 11 , wherein the restriction is a restriction on personal identifiable data communicated from the electronic device.

13. The method of claim 1 , wherein the recommended action is generated using a machine learning process.

14. A system for management of a user's privacy preferences, comprising:

an electronic device comprising at least one computer processor;

a privacy policy manager program executed by a server;

a privacy policy manager computer application executed by the electronic device; and

a computer application or browser executed by the electronic device that accessed a website;

wherein:

the privacy policy manager computer application identifies the computer application or the website accessed using the browser by examining network traffic to and from the electronic device via a network monitor separate from the user electronic device;

the privacy policy manager computer application retrieves, from the privacy policy manager program, a privacy policy document analysis for a privacy policy document associated with the computer application or the website, the privacy policy document analysis comprising a valuation of a plurality of privacy policy segments within the privacy policy document;

the privacy policy manager computer application receives a privacy preference analysis for the user, the privacy preference analysis comprising a valuation of a plurality of privacy preferences for the user;

the privacy policy manager computer application identifies a recommended action in response to the valuation of one of the privacy policy segments being outside the scope of the valuation of one of the plurality of privacy preferences; and

the privacy policy manager computer application executes the recommended action.

15. The system of claim 14 , wherein the privacy policy manager program generates the privacy policy document analysis using natural language processing of the privacy policy document.

16. The system of claim 14 , wherein each privacy policy segment comprises a privacy category, a privacy sub-category, and a privacy sub-category classification, and the valuation of the privacy policy segment is based on at least one of the privacy sub-category and the privacy sub-category classification for the privacy policy segment.

17. The system of claim 14 , wherein the recommended action is based on at least one of an action taken by a second user and news related to an entity associated with the application or website.

18. The system of claim 14 , wherein the recommendation is to restrict personal identifiable data communicated from the electronic device.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 28, 2024
From: BONAT, MICHELLE; DAO, TUAN; BACHELOR, RODERIC; BENNETT, JEREMY F.; DARMO, RALPH; GRIGNON, ANDREW; MOYNAHAN, KATHLEEN
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 066582/0519 →
Continuity (3)
Provisional Application 62874240 · Jul 15, 2019
Provisional Application 62856491 · Jun 3, 2019
Related Publication 20200380171A1 · Dec 3, 2020
Cited By (2)
US 12,585,823 US 12,626,019