Patents by Inventor Visvanathan Thothathri

Visvanathan Thothathri 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).

  • Machine learning model abstraction layer for runtime efficiency
    Patent number: 11861472
    Abstract: Systems and methods include receiving a trained machine learning model that has been processed with training information removed therefrom, wherein the training information is utilized in training of the trained machine learning model; monitoring traffic, inline at the node, including processing the traffic with the trained machine learning model; obtaining a verdict on the traffic based on the trained machine learning model; and performing an action on the traffic based on the verdict.
    Type: Grant
    Filed: September 29, 2022
    Date of Patent: January 2, 2024
    Assignee: Zscaler, Inc.
    Inventors: Rex Shang, Dianhuan Lin, Changsha Ma, Douglas A. Koch, Shashank Gupta, Parnit Sainion, Visvanathan Thothathri, Narinder Paul, Howie Xu
  • Machine learning model abstraction layer for runtime efficiency
    Publication number: 20230018188
    Abstract: Systems and methods include receiving a trained machine learning model that has been processed with training information removed therefrom, wherein the training information is utilized in training of the trained machine learning model; monitoring traffic, inline at the node, including processing the traffic with the trained machine learning model; obtaining a verdict on the traffic based on the trained machine learning model; and performing an action on the traffic based on the verdict.
    Type: Application
    Filed: September 29, 2022
    Publication date: January 19, 2023
    Inventors: Rex Shang, Dianhuan Lin, Changsha Ma, Douglas A. Koch, Shashank Gupta, Parnit Sainion, Visvanathan Thothathri, Narinder Paul, Howie Xu
  • Machine learning model abstraction layer for runtime efficiency
    Patent number: 11475368
    Abstract: Systems and methods include training a machine learning model with data for identifying features in monitored traffic in a network; analyzing the trained machine learning model to identify information overhead therein, wherein the information overhead is utilized in part for the training; removing the information overhead in the machine learning model; and providing the machine learning model for runtime use for identifying the features in the monitored traffic, with the removed information overhead from the machine learning model.
    Type: Grant
    Filed: September 18, 2020
    Date of Patent: October 18, 2022
    Assignee: Zscaler, Inc.
    Inventors: Rex Shang, Dianhuan Lin, Changsha Ma, Douglas A. Koch, Shashank Gupta, Parnit Sainion, Visvanathan Thothathri, Narinder Paul, Howie Xu
  • Machine learning model abstraction layer for runtime efficiency
    Publication number: 20210004726
    Abstract: Systems and methods include training a machine learning model with data for identifying features in monitored traffic in a network; analyzing the trained machine learning model to identify information overhead therein, wherein the information overhead is utilized in part for the training; removing the information overhead in the machine learning model; and providing the machine learning model for runtime use for identifying the features in the monitored traffic, with the removed information overhead from the machine learning model.
    Type: Application
    Filed: September 18, 2020
    Publication date: January 7, 2021
    Inventors: Rex Shang, Dianhuan Lin, Changsha Ma, Douglas A. Koch, Shashank Gupta, Parnit Sainion, Visvanathan Thothathri, Narinder Paul, Howie Xu