Patents by Inventor Eamon Hirata Jordan

Eamon Hirata Jordan 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).

  • Publication number: 20200364620
    Abstract: Testing machine learning sensors by adding obfuscated training data to test data, and performing real time model fit analysis on live network traffic to determine whether to retrain.
    Type: Application
    Filed: July 23, 2020
    Publication date: November 19, 2020
    Applicant: Resurgo, LLC
    Inventors: Eamon Hirata Jordan, Chad Kumao Takahashi, Ryan Susumu Ito
  • Publication number: 20200356904
    Abstract: Testing machine learning sensors by adding obfuscated training data to test data, and performing real time model fit analysis on live network traffic to determine whether to retrain.
    Type: Application
    Filed: July 31, 2020
    Publication date: November 12, 2020
    Applicant: Resurgo, LLC
    Inventors: Eamon Hirata Jordan, Chad Kumao Takahashi, Ryan Susumu Ito
  • Patent number: 10733530
    Abstract: Testing machine learning sensors by adding obfuscated training data to test data, and performing real time model fit analysis on live network traffic to determine whether to retrain.
    Type: Grant
    Filed: December 8, 2016
    Date of Patent: August 4, 2020
    Assignee: RESURGO, LLC
    Inventors: Eamon Hirata Jordan, Chad Kumao Takahashi, Ryan Susumu Ito
  • Publication number: 20180165597
    Abstract: Testing machine learning sensors by adding obfuscated training data to test data, and performing real time model fit analysis on live network traffic to determine whether to retrain.
    Type: Application
    Filed: December 8, 2016
    Publication date: June 14, 2018
    Applicant: RESURGO, LLC
    Inventors: EAMON HIRATA JORDAN, CHAD KUMAO TAKAHASHI, RYAN SUSUMU ITO, MATTHEW DAVID-KRISTOFER TROGLIA
  • Publication number: 20150052609
    Abstract: Heterogeneous sensors simultaneously inspect network traffic for attacks. A signature-based sensor detects known attacks but has a blind spot, and a machine-learning based sensor that has been trained to detect attacks in the blind spot detects attacks that fail to conform to normal network traffic. False positive rates of the machine-learning based sensor are reduced by iterative testing using statistical techniques.
    Type: Application
    Filed: November 3, 2014
    Publication date: February 19, 2015
    Applicant: RESURGO, LLC
    Inventors: Eamon Hirata Jordan, Kevin Barry Jordan, Evan Joseph Kelly
  • Patent number: 8887285
    Abstract: Heterogeneous sensors simultaneously inspect network traffic for attacks. A signature-based sensor detects known attacks but has a blind spot, and a machine-learning based sensor that has been trained to detect attacks in the blind spot detects attacks that fail to conform to normal network traffic. False positive rates of the machine-learning based sensor are reduced by iterative testing using statistical techniques.
    Type: Grant
    Filed: March 14, 2013
    Date of Patent: November 11, 2014
    Assignee: Resurgo, LLC
    Inventors: Eamon Hirata Jordan, Evan Joseph Kelly, Kevin Barry Jordan
  • Publication number: 20140283052
    Abstract: Heterogeneous sensors simultaneously inspect network traffic for attacks. A signature-based sensor detects known attacks but has a blind spot, and a machine-learning based sensor that has been trained to detect attacks in the blind spot detects attacks that fail to conform to normal network traffic. False positive rates of the machine-learning based sensor are reduced by iterative testing using statistical techniques.
    Type: Application
    Filed: March 14, 2013
    Publication date: September 18, 2014
    Inventors: Eamon Hirata Jordan, Evan Joseph Kelly, Kevin Barry Jordan