Patents by Inventor James Coggeshall

James Coggeshall 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).

  • SYSTEM AND METHOD FOR EMPIRICAL ORGANIZATIONAL CYBERSECURITY RISK ASSESSMENT USING EXTERNALLY-VISIBLE DATA
    Publication number: 20200396246
    Abstract: A system and method for assessing the cybersecurity breach risk associated with a given organization is disclosed. The system and method assume no internal visibility into any organizational network. A taxonomy of possible data sources is defined and motivated. The system and method are both purely empirical and robust against common difficulties in scoring organizational networks, such as the raw number of network assets owned by the organization.
    Type: Application
    Filed: August 31, 2020
    Publication date: December 17, 2020
    Inventors: Scott Michael Zoldi, James Coggeshall
  • System and method for empirical organizational cybersecurity risk assessment using externally-visible data
    Patent number: 10791136
    Abstract: A system and method for assessing the cybersecurity breach risk associated with a given organization is disclosed. The system and method assume no internal visibility into any organizational network. A taxonomy of possible data sources is defined and motivated. The system and method are both purely empirical and robust against common difficulties in scoring organizational networks, such as the raw number of network assets owned by the organization.
    Type: Grant
    Filed: March 20, 2017
    Date of Patent: September 29, 2020
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Scott Michael Zoldi, James Coggeshall
  • System and Method for Empirical Organizational Cybersecurity Risk Assessment Using Externally-Visible Data
    Publication number: 20180270266
    Abstract: A system and method for assessing the cybersecurity breach risk associated with a given organization is disclosed. The system and method assume no internal visibility into any organizational network. A taxonomy of possible data sources is defined and motivated. The system and method are both purely empirical and robust against common difficulties in scoring organizational networks, such as the raw number of network assets owned by the organization.
    Type: Application
    Filed: March 20, 2017
    Publication date: September 20, 2018
    Inventors: Scott Michael Zoldi, James Coggeshall