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:
Jul. 11, 2023

Filed:

May. 02, 2017
Applicant:

Privitar Limited, Cambridge, GB;

Inventors:

Jason Derek McFall, Cambridge, GB;

Charles Codman Cabot, Cambridge, GB;

Timothy James Moran, Cambridge, GB;

Kieron Francois Pascal Guinamard, Cambridge, GB;

Vladimir Michael Eatwell, Cambridge, GB;

Benjamin Thomas Pickering, Cambridge, GB;

Paul David Mellor, Cambridge, GB;

Theresa Stadler, Cambridge, GB;

Andrei Petre, Cambridge, GB;

Christopher Andrew Smith, Cambridge, GB;

Anthony Jason Du Preez, Cambridge, GB;

Igor Vujosevic, Cambridge, GB;

George Danezis, Cambridge, GB;

Assignee:

PRIVITAR LIMITED, Cambridge, GB;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 21/62 (2013.01); G06F 21/60 (2013.01); G06F 21/78 (2013.01); H04L 9/00 (2022.01); H04L 9/08 (2006.01); H04L 9/32 (2006.01);
U.S. Cl.
CPC ...
G06F 21/6254 (2013.01); G06F 21/602 (2013.01); G06F 21/78 (2013.01); H04L 9/008 (2013.01); H04L 9/0825 (2013.01); H04L 9/0844 (2013.01); H04L 9/0866 (2013.01); H04L 9/3247 (2013.01);
Abstract

A system allows the identification and protection of sensitive data in a multiple ways, which can be combined for different workflows, data situations or use cases. The system scans datasets to identify sensitive data or identifying datasets, and to enable the anonymisation of sensitive or identifying datasets by processing that data to produce a safe copy. Furthermore, the system prevents access to a raw dataset. The system enables privacy preserving aggregate queries and computations. The system uses differentially private algorithms to reduce or prevent the risk of identification or disclosure of sensitive information. The system scales to big data and is implemented in a way that supports parallel execution on a distributed compute cluster.


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