The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Oct. 17, 2023
Filed:
Mar. 31, 2021
Microsoft Technology Licensing, Llc, Redmond, WA (US);
Haifeng Zhao, San Jose, CA (US);
Yang Chen, Sunnyvale, CA (US);
Jiashuo Wang, Mountain View, CA (US);
Xiaojing Chen, Santa Clara, CA (US);
Chencheng Wu, Los Altos, CA (US);
Souvik Ghosh, Saratoga, CA (US);
Ankit Gupta, Fremont, CA (US);
Jing Wang, Los Altos, CA (US);
John Patrick Moore, San Francisco, CA (US);
Henry Heyburn Pistell, Ridgewood, NJ (US);
Mira Thambireddy, San Mateo, CA (US);
Haowen Cao, Sunnyvale, CA (US);
Keyi Yu, Mountain View, CA (US);
Microsoft Technology Licensing, LLC, Redmond, WA (US);
Abstract
Techniques for a flexible data security and machine learning system for merging third-party data are provided. In one technique, the system receives a data set from a third-party entity and receives selection data that indicates that the third-party entity selected a set of data security policies that includes an encryption option and a data mixing option from among multiple data mixing options. In response to receiving the selection data, the system stores data that associates the set of data security policies with the data set, encrypts the data set according to the encryption option, and persistently stores the encrypted data set. Later, the system decrypts the encrypted data set in volatile memory, generates, based on the data mixing option, training data based on the decrypted version of the data set, trains a machine-learned model based on the training data, and stores the machine-learned model in association with the data set.