Patents by Inventor Christian Lebiere

Christian Lebiere 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: 11494486
    Abstract: Described is a system for continuously predicting and adapting optimal strategies for attacker elicitation. The system includes a global bot controlling processor unit and one or more local bot controlling processor units. The global bot controlling processor unit includes a multi-layer network software unit for extracting attacker features from diverse, out-of-band (OOB) media sources. The global controlling processing unit further includes an adaptive behavioral game theory (GT) software unit for determining a best strategy for eliciting identifying information from an attacker. Each local bot controlling processor unit includes a cognitive model (CM) software unit for estimating a cognitive state of the attacker and predicting attacker behavior. A generative adversarial network (GAN) software unit predicts the attacker's strategies.
    Type: Grant
    Filed: November 14, 2019
    Date of Patent: November 8, 2022
    Assignee: HRL LABORATORIES, LLC
    Inventors: Hyun (Tiffany) J. Kim, Rajan Bhattacharyya, Samuel D. Johnson, Soheil Kolouri, Christian Lebiere, Jiejun Xu
  • Patent number: 10569772
    Abstract: Described is a system for predicting the behavior of an autonomous system. The system identifies a taxonomic state of a motion condition of an autonomous vehicle based on a spatiotemporal location of the autonomous vehicle and elements of a driving scenario. Behavior of the autonomous vehicle is predicted based on the taxonomic state of the motion condition. The autonomous vehicle makes and implements a driving operation decision based on the predicted behavior.
    Type: Grant
    Filed: April 6, 2018
    Date of Patent: February 25, 2020
    Assignee: HRL Laboratories, LLC
    Inventors: Hyun (Tiffany) J. Kim, Christian Lebiere, Jerry Vinokurov, Rajan Bhattacharyya
  • Patent number: 10176438
    Abstract: Embodiments of a system and method for identifying malware tasks using a controlled environment to run malicious software to generate analysis reports, a parser to extract features from the analysis reports and a cognitively inspired learning algorithm to predict tasks associated with the malware are disclosed.
    Type: Grant
    Filed: June 17, 2016
    Date of Patent: January 8, 2019
    Assignees: Arizona Board of Regents on Behalf of Arizona State University, Carnegie Mellon University
    Inventors: Paulo Shakarian, Eric Nunes, Casey Buto, Christian Lebiere, Robert Thomson, Stefano Bennati
  • Publication number: 20180297592
    Abstract: Described is a system for predicting the behavior of an autonomous system. The system identifies a taxonomic state of a motion condition of an autonomous vehicle based on a spatiotemporal location of the autonomous vehicle and elements of a driving scenario. Behavior of the autonomous vehicle is predicted based on the taxonomic state of the motion condition. The autonomous vehicle makes and implements a driving operation decision based on the predicted behavior.
    Type: Application
    Filed: April 6, 2018
    Publication date: October 18, 2018
    Inventors: Hyun (Tiffany) J. Kim, Christian Lebiere, Jerry Vinokurov, Rajan Bhattacharyya
  • Publication number: 20160371490
    Abstract: Embodiments of a system and method for identifying malware tasks using a controlled environment to run malicious software to generate analysis reports, a parser to extract features from the analysis reports and a cognitively inspired learning algorithm to predict tasks associated with the malware are disclosed.
    Type: Application
    Filed: June 17, 2016
    Publication date: December 22, 2016
    Inventors: Paulo Shakarian, Eric Nunes, Casey Buto, Christian Lebiere, Robert Thomson, Stefano Bennati