Patents by Inventor Kristine M. Arthur

Kristine M. Arthur 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).

  • Patent number: 10833954
    Abstract: A network analysis tool receives network flow information and uses deep learning—machine learning that models high-level abstractions in the network flow information—to identify dependencies between network assets. Based on the identified dependencies, the network analysis tool can discover functional relationships between network assets. For example, a network analysis tool receives network flow information, identifies dependencies between multiple network assets based on evaluation of the network flow information, and outputs results of the identification of the dependencies. When evaluating the network flow information, the network analysis tool can pre-process the network flow information to produce input vectors, use deep learning to extract patterns in the input vectors, and then determine dependencies based on the extracted patterns. The network analysis tool can repeat this process so as to update an assessment of the dependencies between network assets on a near real-time basis.
    Type: Grant
    Filed: November 19, 2014
    Date of Patent: November 10, 2020
    Assignee: Battelle Memorial Institute
    Inventors: Thomas E. Carroll, Satish Chikkagoudar, Thomas W. Edgar, Kiri J. Oler, Kristine M. Arthur, Daniel M. Johnson, Lars J. Kangas
  • Patent number: 10637744
    Abstract: A network analysis tool evaluates network flow information in complementary workflows to identify one-hop behavior of network assets and also identify multi-hop dependencies between network assets. In one workflow (e.g., using association rule learning), the network analysis tool can identify significant one-hop communication patterns to and/or from network assets, taken individually. Based on the identified one-hop behavior, the network analysis tool can discover patterns of similar communication among different network assets, which can inform decisions about deploying patch sets, mitigating damage, configuring a system, or detecting anomalous behavior. In a different workflow (e.g., using deep learning or cross-correlation analysis), the network analysis tool can identify significant multi-hop communication patterns that involve network assets in combination.
    Type: Grant
    Filed: April 12, 2017
    Date of Patent: April 28, 2020
    Assignee: Battelle Memorial Institute
    Inventors: Thomas E. Carroll, Satish Chikkagoudar, Kristine M. Arthur-Durett, Dennis G. Thomas
  • Publication number: 20180302306
    Abstract: A network analysis tool evaluates network flow information in complementary workflows to identify one-hop behavior of network assets and also identify multi-hop dependencies between network assets. In one workflow (e.g., using association rule learning), the network analysis tool can identify significant one-hop communication patterns to and/or from network assets, taken individually. Based on the identified one-hop behavior, the network analysis tool can discover patterns of similar communication among different network assets, which can inform decisions about deploying patch sets, mitigating damage, configuring a system, or detecting anomalous behavior. In a different workflow (e.g., using deep learning or cross-correlation analysis), the network analysis tool can identify significant multi-hop communication patterns that involve network assets in combination.
    Type: Application
    Filed: April 12, 2017
    Publication date: October 18, 2018
    Inventors: Thomas E. Carroll, Satish Chikkagoudar, Kristine M. Arthur-Durett, Dennis G. Thomas
  • Publication number: 20160142266
    Abstract: A network analysis tool receives network flow information and uses deep learning—machine learning that models high-level abstractions in the network flow information—to identify dependencies between network assets. Based on the identified dependencies, the network analysis tool can discover functional relationships between network assets. For example, a network analysis tool receives network flow information, identifies dependencies between multiple network assets based on evaluation of the network flow information, and outputs results of the identification of the dependencies. When evaluating the network flow information, the network analysis tool can pre-process the network flow information to produce input vectors, use deep learning to extract patterns in the input vectors, and then determine dependencies based on the extracted patterns. The network analysis tool can repeat this process so as to update an assessment of the dependencies between network assets on a near real-time basis.
    Type: Application
    Filed: November 19, 2014
    Publication date: May 19, 2016
    Applicant: BATTELLE MEMORIAL INSTITUTE
    Inventors: Thomas E. Carroll, Satish Chikkagoudar, Thomas W. Edgar, Kiri J. Oler, Kristine M. Arthur, Daniel M. Johnson, Lars J. Kangas