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.

Date of Patent:
May. 24, 2022

Filed:

Mar. 05, 2020
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Anjaneya Malpani, Bellevue, WA (US);

Jagadeesh Virupaksha Huliyar, Redmond, WA (US);

Xinyun Sun, Kirkland, WA (US);

Sreeram Nivarthi, Redmond, WA (US);

Muthukrishnan Paramasivam, Seattle, WA (US);

Dheepak Ramaswamy, Seattle, WA (US);

Sriradha Selvaraj, Redmond, WA (US);

Ananthatejas Raghavan, Redmond, WA (US);

Sergey Yekhanin, Redmond, WA (US);

Janardhan Kulkarni, Seattle, WA (US);

Aleksey Ashikhmin, Redmond, WA (US);

Sivakanth Gopi, Redmond, WA (US);

Bingran Luo, Bellevue, WA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04K 1/02 (2006.01); H04W 12/02 (2009.01); G06F 16/248 (2019.01); H04L 41/08 (2022.01); H03M 13/39 (2006.01); H03M 13/41 (2006.01); H03M 13/00 (2006.01);
U.S. Cl.
CPC ...
H04K 1/02 (2013.01); G06F 16/248 (2019.01); H04L 41/0883 (2013.01); H04W 12/02 (2013.01); H03M 13/3961 (2013.01); H03M 13/4107 (2013.01); H03M 13/4192 (2013.01); H03M 13/6502 (2013.01);
Abstract

A system and method for applying noise to data is described. The system accesses a metric value of a metric of each user from a group of users of an application. The metric indicates a measure of an operation of the application by a corresponding user. The system generates noise values and defines a distribution of the noise values to the group of users. The system modifies the metric value of the metric of each user with a corresponding noise value from the noise values based on the distribution.


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