Patents by Inventor Rafal MZYK

Rafal MZYK 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).

  • Pluggable data taxonomy and processing
    Patent number: 12682095
    Abstract: A taxonomy-agnostic data protection framework includes a plugged-in data classification taxonomy definition having a taxonomy identifier and a set of data classification indicators. The taxonomy-agnostic data protection framework also includes a plugged-in set of data classification processing routines, and a plugged-in mapping mechanism which maps between data classification processing routines and data classification indicators. The framework facilitates efficient, accurate, and thorough implementation of data classification propagation per the plugged-in taxonomy, both within a given program and between programs that connect over a network. The framework also facilitates flexible implementation of per-taxonomy data protection actions such as deletion, redaction, encryption, anonymization, pseudonymization, hashing, or enrichment, in response to individual or combined data classification indicators.
    Type: Grant
    Filed: May 16, 2023
    Date of Patent: July 14, 2026
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Martin Taillefer, Rafal Mzyk, Andrey Noskov, Ján Guttek, Scott Allen Thurlow, Stephen Toub
  • PLUGGABLE DATA TAXONOMY AND PROCESSING
    Publication number: 20240386122
    Abstract: A taxonomy-agnostic data protection framework includes a plugged-in data classification taxonomy definition having a taxonomy identifier and a set of data classification indicators. The taxonomy-agnostic data protection framework also includes a plugged-in set of data classification processing routines, and a plugged-in mapping mechanism which maps between data classification processing routines and data classification indicators. The framework facilitates efficient, accurate, and thorough implementation of data classification propagation per the plugged-in taxonomy, both within a given program and between programs that connect over a network. The framework also facilitates flexible implementation of per-taxonomy data protection actions such as deletion, redaction, encryption, anonymization, pseudonymization, hashing, or enrichment, in response to individual or combined data classification indicators.
    Type: Application
    Filed: May 16, 2023
    Publication date: November 21, 2024
    Inventors: Martin TAILLEFER, Rafal MZYK, Andrey NOSKOV, Ján GUTTEK, Scott Allen THURLOW, Stephen TOUB