Patents by Inventor Bryan Doyle

Bryan Doyle 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).

  • Predicting cyber risk for assets with limited scan information using machine learning
    Patent number: 12335298
    Abstract: Techniques, methods and/or apparatuses are disclosed that enable prediction of cyber risks of assets of networks. Through the disclosed techniques, a cyber risk prediction model, which may be a form of a machine learning model, may be trained to predict cyber risks. The cyber risk model may be provided to a cyber risk predictor two predict cyber risks of an asset, without the need to scan the asset at a very deep scan level.
    Type: Grant
    Filed: October 2, 2023
    Date of Patent: June 17, 2025
    Assignee: Tenable, Inc.
    Inventors: Damien McParland, Bryan Doyle, Vincent Gilcreest, Renaud Deraison
  • Continuous scoring of security controls and dynamic tuning of security policies
    Patent number: 11973788
    Abstract: Techniques, methods and/or apparatuses are disclosed that enable of cyber risks on assets of networks to be evaluated in presence of security controls on the assets. In this way, effect of security controls already in place may be quantified. A novel scoring technique is presented. Also, use of causal inference is in the context of security risk assessment is described.
    Type: Grant
    Filed: March 8, 2021
    Date of Patent: April 30, 2024
    Assignee: TENABLE, INC.
    Inventors: Aditya Kuppa, Lamine Aouad, Bryan Doyle
  • PREDICTING CYBER RISK FOR ASSETS WITH LIMITED SCAN INFORMATION USING MACHINE LEARNING
    Publication number: 20240031396
    Abstract: Techniques, methods and/or apparatuses are disclosed that enable prediction of cyber risks of assets of networks. Through the disclosed techniques, a cyber risk prediction model, which may be a form of a machine learning model, may be trained to predict cyber risks. The cyber risk model may be provided to a cyber risk predictor two predict cyber risks of an asset, without the need to scan the asset at a very deep scan level.
    Type: Application
    Filed: October 2, 2023
    Publication date: January 25, 2024
    Inventors: Damien McParland, Bryan Doyle, Vincent Gilcreest, Renaud Deraison
  • Predicting cyber risk for assets with limited scan information using machine learning
    Patent number: 11818160
    Abstract: Techniques, methods and/or apparatuses are disclosed that enable prediction of cyber risks of assets of networks. Through the disclosed techniques, a cyber risk prediction model, which may be a form of a machine learning model, may be trained to predict cyber risks. The cyber risk model may be provided to a cyber risk predictor two predict cyber risks of an asset, without the need to scan the asset at a very deep scan level.
    Type: Grant
    Filed: February 22, 2021
    Date of Patent: November 14, 2023
    Assignee: TENABLE, INC.
    Inventors: Damien McParland, Bryan Doyle, Vincent Gilcreest, Renaud Deraison
  • CONTINUOUS SCORING OF SECURITY CONTROLS AND DYNAMIC TUNING OF SECURITY POLICIES
    Publication number: 20220286474
    Abstract: Techniques, methods and/or apparatuses are disclosed that enable of cyber risks on assets of networks to be evaluated in presence of security controls on the assets. In this way, effect of security controls already in place may be quantified. A novel scoring technique is presented. Also, use of causal inference is in the context of security risk assessment is described.
    Type: Application
    Filed: March 8, 2021
    Publication date: September 8, 2022
    Inventors: Aditya KUPPA, Lamine AOUAD, Bryan Doyle
  • PREDICTING CYBER RISK FOR ASSETS WITH LIMITED SCAN INFORMATION USING MACHINE LEARNING
    Publication number: 20220272115
    Abstract: Techniques, methods and/or apparatuses are disclosed that enable prediction of cyber risks of assets of networks. Through the disclosed techniques, a cyber risk prediction model, which may be a form of a machine learning model, may be trained to predict cyber risks. The cyber risk model may be provided to a cyber risk predictor two predict cyber risks of an asset, without the need to scan the asset at a very deep scan level.
    Type: Application
    Filed: February 22, 2021
    Publication date: August 25, 2022
    Inventors: Damien McParland, Bryan Doyle, Vincent Gilcreest, Renaud DERAISON