Patents by Inventor Zachariah Thomas Pelletier

Zachariah Thomas Pelletier 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).

  • Generating synthetic test cases for network fuzz testing
    Patent number: 11762761
    Abstract: A system for generating synthetic test cases for fuzz testing. One example includes an electronic processor. The electronic processor is configured to pre-process training data, use the training data to train a discriminator DNN to evaluate a test case to determine whether the test case is likely to expose a software vulnerability, and use the discriminator DNN to train a generator DNN to generate a test case that is likely to expose a software vulnerability. The electronic processor uses the discriminator DNN to train the generator DNN by determining whether a test case generated by the generator DNN is likely to expose a software vulnerability and sending a determination of whether the test case generated by the generator DNN is likely to expose a software vulnerability to the generator DNN. The electronic processor is further configured to, when the generator DNN is trained, generate one or more test cases.
    Type: Grant
    Filed: February 3, 2022
    Date of Patent: September 19, 2023
    Assignee: Robert Bosch GmbH
    Inventors: John McShane, Timothy S. Arntson, Zachariah Thomas Pelletier
  • GENERATING SYNTHETIC TEST CASES FOR NETWORK FUZZ TESTING
    Publication number: 20220269591
    Abstract: A system for generating synthetic test cases for fuzz testing. One example includes an electronic processor. The electronic processor is configured to pre-process training data, use the training data to train a discriminator DNN to evaluate a test case to determine whether the test case is likely to expose a software vulnerability, and use the discriminator DNN to train a generator DNN to generate a test case that is likely to expose a software vulnerability. The electronic processor uses the discriminator DNN to train the generator DNN by determining whether a test case generated by the generator DNN is likely to expose a software vulnerability and sending a determination of whether the test case generated by the generator DNN is likely to expose a software vulnerability to the generator DNN. The electronic processor is further configured to, when the generator DNN is trained, generate one or more test cases.
    Type: Application
    Filed: February 3, 2022
    Publication date: August 25, 2022
    Inventors: John McShane, Timothy S. Arntson, Zachariah Thomas Pelletier