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:
Jun. 01, 2021

Filed:

May. 22, 2018
Applicants:

Georgetown University, Washington, DC (US);

President and Fellows of Harvard College, Cambridge, MA (US);

The Regents of the University of California, Oakland, CA (US);

Inventors:

Yaacov Nissim Kobliner, Brookline, MA (US);

Uri Stemmer, Cambridge, MA (US);

Raef Bahi Youssef Bassily, San Diego, CA (US);

Abhradeep Guha Thakurta, Santa Cruz, CA (US);

Assignee:

Georgetown University, Washington, DC (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 21/60 (2013.01); H04L 9/06 (2006.01); G06F 21/62 (2013.01);
U.S. Cl.
CPC ...
G06F 21/602 (2013.01); G06F 21/6245 (2013.01); H04L 9/0643 (2013.01); H04L 2209/08 (2013.01);
Abstract

Technologies are disclosed for computing heavy hitter histograms using locally private randomization. Under this strategy, 'agents' can each hold a 'type' derived from a large dictionary. By performing an algorithm, an estimate of the distribution of data can be obtained. Two algorithms implement embodiments for performing methods involving differential privacy for one or more users, and usually are run in the local model. This means that information is collected from the agents with added noise to hide the agents' individual contributions to the histogram. The result is an accurate enough estimate of the histogram for commercial or other applications relating to the data collection of one or more agents. Specifically, the proposed algorithms improve on the performance (measured in computation and memory requirements at the server and the agent, as well as communication volume) of previously solutions.


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