Patents by Inventor Sonal Lalchand OSWAL

Sonal Lalchand OSWAL 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).

  • System and method for detecting bots using semi-supervised deep learning techniques
    Patent number: 11627156
    Abstract: A system of method of detecting bots are presented. The method includes receiving access patterns of a visitor accessing a protected web property, encoding each of the access patterns into a fixed length feature vector, determining an offline-trained model based on past data, generating an anomaly score based on the fixed length feature vector and an offline-trained model, and determining the visitor to be a bot, when the generated anomaly score associated with the visitor reaches a predetermined threshold.
    Type: Grant
    Filed: September 18, 2019
    Date of Patent: April 11, 2023
    Assignee: RADWARE LTD.
    Inventors: Harisankar Haridas, Mohit Rajput, Rakesh Thatha, Sonal Lalchand Oswal, Neeraj Kumar Gupta
  • System and method for detecting bots based on anomaly detection of JavaScript or mobile app profile information
    Patent number: 11516235
    Abstract: A system and method for detecting bots. The method includes receiving a request to access a server, the request is being received from a client device, and responsive to the request, causing the client device to download a script code file to the client device. The script code file, when executed, collects a profile, and the profile includes a plurality of parameters. The method also includes receiving the created profile, generating a score based on the plurality of parameters to identify a bot, and initiating a mitigation action based on the identified bot.
    Type: Grant
    Filed: October 3, 2019
    Date of Patent: November 29, 2022
    Assignee: Kaalbi Technologies Private Limited
    Inventors: Neeraj Kumar Gupta, Aman Rawka, Harisankar Haridas, Rakesh Thatha, Sonal Lalchand Oswal
  • SYSTEM AND METHOD FOR DETECTING BOTS BASED ON ANOMALY DETECTION OF JAVASCRIPT OR MOBILE APP PROFILE INFORMATION
    Publication number: 20200112578
    Abstract: A system and method for detecting bots. The method includes receiving a request to access a server, the request is being received from a client device, and responsive to the request, causing the client device to download a script code file to the client device. The script code file, when executed, collects a profile, and the profile includes a plurality of parameters. The method also includes receiving the created profile, generating a score based on the plurality of parameters to identify a bot, and initiating a mitigation action based on the identified bot.
    Type: Application
    Filed: October 3, 2019
    Publication date: April 9, 2020
    Applicant: KAALBI TECHNOLOGIES PRIVATE LIMITED
    Inventors: Neeraj Kumar GUPTA, Aman RAWKA, Harisankar HARIDAS, Rakesh THATHA, Sonal Lalchand OSWAL
  • SYSTEM AND METHOD FOR DETECTING BOTS BASED ON ITERATIVE CLUSTERING AND FEEDBACK-DRIVEN ADAPTIVE LEARNING TECHNIQUES
    Publication number: 20200099713
    Abstract: A system and method for detecting and blocking bots are presented. The method includes receiving unlabeled data regarding a visitor of a web source, grouping the received unlabeled data with similar characteristics into a group of data, detecting, based on the group of data, at least one anomaly, and determining, based on the at least one detected anomaly, several visitors to be blacklisted.
    Type: Application
    Filed: September 18, 2019
    Publication date: March 26, 2020
    Inventors: Mohit RAJPUT, Harisankar HARIDAS, Rakesh THATHA, Sonal Lalchand OSWAL, Neeraj Kumar GUPTA
  • SYSTEM AND METHOD FOR DETECTING BOTS USING SEMI-SUPERVISED DEEP LEARNING TECHNIQUES
    Publication number: 20200099714
    Abstract: A system of method of detecting bots are presented. The method includes receiving access patterns of a visitor accessing a protected web property, encoding each of the access patterns into a fixed length feature vector, determining an offline-trained model based on past data, generating an anomaly score based on the fixed length feature vector and an offline-trained model, and determining the visitor to be a bot, when the generated anomaly score associated with the visitor reaches a predetermined threshold.
    Type: Application
    Filed: September 18, 2019
    Publication date: March 26, 2020
    Inventors: Harisankar HARIDAS, Mohit RAJPUT, Rakesh THATHA, Sonal Lalchand OSWAL, Neeraj Kumar GUPTA