Patents by Inventor Vladimir Michael EATWELL

Vladimir Michael EATWELL has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • COMPUTER-IMPLEMENTED PRIVACY ENGINEERING SYSTEM AND METHOD
    Publication number: 20230359770
    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.
    Type: Application
    Filed: July 10, 2023
    Publication date: November 9, 2023
    Inventors: Jason Derek MCFALL, Charles Codman CABOT, Timothy James MORAN, Kieron Francois Pascal GUINAMARD, Vladimir Michael EATWELL, Benjamin Thomas PICKERING, Paul David MELLOR, Theresa STADLER, Andrei PETRE, Christopher Andrew SMITH, Anthony Jason DU PREEZ, Igor VUJOSEVIC, George DANEZIS
  • Computer-implemented privacy engineering system and method
    Patent number: 11698990
    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.
    Type: Grant
    Filed: May 2, 2017
    Date of Patent: July 11, 2023
    Assignee: PRIVITAR LIMITED
    Inventors: Jason Derek McFall, Charles Codman Cabot, Timothy James Moran, Kieron Francois Pascal Guinamard, Vladimir Michael Eatwell, Benjamin Thomas Pickering, Paul David Mellor, Theresa Stadler, Andrei Petre, Christopher Andrew Smith, Anthony Jason Du Preez, Igor Vujosevic, George Danezis
  • COMPUTER-IMPLEMENTED PRIVACY ENGINEERING SYSTEM AND METHOD
    Publication number: 20200327252
    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.
    Type: Application
    Filed: May 2, 2017
    Publication date: October 15, 2020
    Inventors: Jason Derek MCFALL, Charles Codman CABOT, Timothy James MORAN, Kieron Francois Pascal GUINAMARD, Vladimir Michael EATWELL, Benjamin Thomas PICKERING, Paul David MELLOR, Theresa STADLER, Andrei PETRE, Christopher Andrew SMITH, Anthony Jason DU PREEZ, Igor VUJOSEVIC, George DANEZIS