Patents by Inventor Toshal Phene

Toshal Phene 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).

  • DETERMINING A RISK PROBABILITY OF A URL USING MACHINE LEARNING OF URL SEGMENTS
    Publication number: 20220286483
    Abstract: Systems, methods, and apparatuses enable a machine learning model to determine a risk probability of a URL. A query configurator receives a URL in a query and normalizes the URL. The normalized URL is segmented into a plurality of segments. The plurality of segments is serially provided to the machine learning model trained to provide an indication of risk associated with the URL. The indication of risk associated with the URL can be a probability value based on one or more risk probabilities determined for segment-segment transitions of the URL. A security service compares the probability value of the URL to a threshold value and performs a security action based on a result of comparing the probability value to the threshold value.
    Type: Application
    Filed: May 20, 2022
    Publication date: September 8, 2022
    Applicant: Fortinet, Inc.
    Inventors: Rajiv Sreedhar, Ratinder Paul Singh Ahuja, Manuel Nedbal, Toshal Phene, Jitendra Gaitonde
  • Determining a risk probability of a URL using machine learning of URL segments
    Patent number: 11368486
    Abstract: Systems, methods, and apparatuses enable a machine learning model to determine a risk probability of a URL. A query configurator receives a URL in a query and normalizes the URL. The normalized URL is segmented into a plurality of segments. The plurality of segments is serially provided to the machine learning model trained to provide an indication of risk associated with the URL. The indication of risk associated with the URL can be a probability value based on one or more risk probabilities determined for segment-segment transitions of the URL. A security service compares the probability value of the URL to a threshold value and performs a security action based on a result of comparing the probability value to the threshold value.
    Type: Grant
    Filed: March 12, 2019
    Date of Patent: June 21, 2022
    Assignee: Fortinet, Inc.
    Inventors: Rajiv Sreedhar, Ratinder Paul Singh Ahuja, Manuel Nedbal, Toshal Phene, Jitendra Gaitonde
  • DETERMINING A RISK PROBABILITY OF A URL USING MACHINE LEARNING OF URL SEGMENTS
    Publication number: 20200296134
    Abstract: Systems, methods, and apparatuses enable a machine learning model to determine a risk probability of a URL. A query configurator receives a URL in a query and normalizes the URL. The normalized URL is segmented into a plurality of segments. The plurality of segments is serially provided to the machine learning model trained to provide an indication of risk associated with the URL. The indication of risk associated with the URL can be a probability value based on one or more risk probabilities determined for segment-segment transitions of the URL. A security service compares the probability value of the URL to a threshold value and performs a security action based on a result of comparing the probability value to the threshold value.
    Type: Application
    Filed: March 12, 2019
    Publication date: September 17, 2020
    Inventors: Rajiv Sreedhar, Ratinder Paul Singh Ahuja, Manuel Nedbal, Toshal Phene, Jitendra Gaitonde