Patents by Inventor Prashant Subbarao

Prashant Subbarao 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: 11681936
    Abstract: Systems and methods are disclosed to infer, using a machine learned model, a service protocol of a server based on the banner data produced by the server. In embodiments, the machine learned model is implemented by a network scanner configured to receive banner data from open ports on servers. A received banner is parsed into a set of features, such as the counts or presence of particular characters or strings in the banner. In embodiments, certain types of banner content such as network addresses, hostnames, dates, and times, are replaced with special characters. The machine learned model is applied to the features to infer a most likely protocol of the server port that produced the banner. Advantageously, the model can be trained to perform the inference task with high accuracy and without using human-specified rules, which can be brittle for unconventional banner data and carry undesired biases.
    Type: Grant
    Filed: October 12, 2022
    Date of Patent: June 20, 2023
    Assignee: Rapid7, Inc.
    Inventors: Roy Hodgman, Derek Abdine, Thomas Sellers, Prashant Subbarao
  • Publication number: 20230034866
    Abstract: Systems and methods are disclosed to infer, using a machine learned model, a service protocol of a server based on the banner data produced by the server. In embodiments, the machine learned model is implemented by a network scanner configured to receive banner data from open ports on servers. A received banner is parsed into a set of features, such as the counts or presence of particular characters or strings in the banner. In embodiments, certain types of banner content such as network addresses, hostnames, dates, and times, are replaced with special characters. The machine learned model is applied to the features to infer a most likely protocol of the server port that produced the banner. Advantageously, the model can be trained to perform the inference task with high accuracy and without using human-specified rules, which can be brittle for unconventional banner data and carry undesired biases.
    Type: Application
    Filed: October 12, 2022
    Publication date: February 2, 2023
    Applicant: Rapid7, Inc.
    Inventors: Roy Hodgman, Derek Abdine, Thomas Sellers, Prashant Subbarao
  • Patent number: 11507860
    Abstract: Systems and methods are disclosed to infer, using a machine learned model, a service protocol of a server based on the banner data produced by the server. In embodiments, the machine learned model is implemented by a network scanner configured to receive banner data from open ports on servers. A received banner is parsed into a set of features, such as the counts or presence of particular characters or strings in the banner. In embodiments, certain types of banner content such as network addresses, hostnames, dates, and times, are replaced with special characters. The machine learned model is applied to the features to infer a most likely protocol of the server port that produced the banner. Advantageously, the model can be trained to perform the inference task with high accuracy and without using human-specified rules, which can be brittle for unconventional banner data and carry undesired biases.
    Type: Grant
    Filed: February 24, 2020
    Date of Patent: November 22, 2022
    Assignee: Rapid7, Inc.
    Inventors: Roy D. Hodgman, Derek Abdine, Thomas E. Sellers, Prashant Subbarao