View source for 18183033. UTILIZING MACHINE-LEARNING MODELS TO DETECT LEAKING SENSITIVE BROWSING INFORMATION simplified abstract (Microsoft Technology Licensing, LLC)

=UTILIZING MACHINE-LEARNING MODELS TO DETECT LEAKING SENSITIVE BROWSING INFORMATION=


==Organization Name==

[[:Category:Microsoft Technology Licensing, LLC|Microsoft Technology Licensing, LLC]]


[[Category:Microsoft Technology Licensing, LLC]]

==Inventor(s)==

[[:Category:John Charles Krumm of Redmond WA (US)|John Charles Krumm of Redmond WA (US)]][[Category:John Charles Krumm of Redmond WA (US)]]

[[:Category:Kyle Robert Crichton of Brooklyn NY (US)|Kyle Robert Crichton of Brooklyn NY (US)]][[Category:Kyle Robert Crichton of Brooklyn NY (US)]]

[[:Category:Siddharth Suri of Redmond WA (US)|Siddharth Suri of Redmond WA (US)]][[Category:Siddharth Suri of Redmond WA (US)]]

[[:Category:Semiha Ece Kamar Eden of Redmond WA (US)|Semiha Ece Kamar Eden of Redmond WA (US)]][[Category:Semiha Ece Kamar Eden of Redmond WA (US)]]

==UTILIZING MACHINE-LEARNING MODELS TO DETECT LEAKING SENSITIVE BROWSING INFORMATION - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18183033 titled 'UTILIZING MACHINE-LEARNING MODELS TO DETECT LEAKING SENSITIVE BROWSING INFORMATION

The disclosure pertains to a sensitivity detection system that accurately identifies when a user's browsing activity unintentionally reveals private or sensitive information about the user. The system utilizes machine learning models to detect sensitivity and takes mitigation actions to prevent the disclosure of sensitive user information.

* Machine learning models are generated and used to detect sensitivity in user information.
* Mitigation actions are taken to stop or reduce the disclosure of sensitive user information.

Potential Applications:
* Data privacy protection in online browsing activities
* Preventing unintentional disclosure of sensitive information
* Enhancing user security and confidentiality

Problems Solved:
* Identifying and preventing the leakage of sensitive user information
* Improving user privacy and data protection in online environments

Benefits:
* Enhanced user privacy and security
* Reduced risk of unintentional disclosure of sensitive information
* Improved trust and confidence in online browsing activities

Commercial Applications:
Title: Data Privacy Protection System for Online Activities
This technology can be used in various industries such as e-commerce, social media platforms, and online service providers to enhance data privacy and security for users. It can also be integrated into web browsers and online platforms to provide users with a safer and more secure browsing experience.

Questions about Data Privacy Protection System for Online Activities:
1. How does the sensitivity detection system ensure the accuracy of identifying sensitive user information?
2. What are the potential implications of this technology for online businesses and service providers?


==Original Abstract Submitted==

The disclosure relates to a sensitivity detection system that accurately and efficiently determines when information based on a user's browsing activity unintentionally reveals private or other sensitive information about the user. For example, the sensitivity detection system generates and utilizes machine learning models for detecting sensitivity to accurately detect when sensitive user information is being leaked from a collection of user information, such as a user profile. Additionally, upon determining that sensitive user information is being revealed, in many instances, the sensitivity detection system performs mitigation actions to stop and/or reduce sensitive user information from being undesirably revealed.



[[Category:G06F21/62]]
[[Category:CPC_G06F21/6254]]