Patents by Inventor Louie Zhang

Louie Zhang 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).

  • Systems and methods for machine learning-based detection of an automated fraud attack or an automated abuse attack
    Patent number: 12047401
    Abstract: A method for machine learning-based detection of an automated fraud or abuse attack includes: identifying, via a computer network, a digital event associated with a suspected automated fraud or abuse attack; composing, via one or more computers, a digital activity signature of the suspected automated fraud or abuse attack based on digital activity associated with the suspected automated fraud or abuse attack; computing, via a machine learning model, an encoded representation of the digital activity signature; searching, via the one or more computers, an automated fraud or abuse signature registry based on the encoded representation of the digital activity signature; determining a likely origin of the digital event based on the searching of the automated fraud or abuse signature registry; and selectively implementing one or more automated threat mitigation actions based on the likely origin of the digital event.
    Type: Grant
    Filed: September 12, 2023
    Date of Patent: July 23, 2024
    Assignee: Sift Science, Inc.
    Inventors: Kostyantyn Gurnov, Wei Liu, Nicholas Benavides, Volha Leusha, Yanqing Bao, Louie Zhang, Irving Chen, Logan Davis, Andy Cai
  • SYSTEMS AND METHODS FOR MACHINE LEARNING-BASED DETECTION OF AN AUTOMATED FRAUD ATTACK OR AN AUTOMATED ABUSE ATTACK
    Publication number: 20230421584
    Abstract: A method for machine learning-based detection of an automated fraud or abuse attack includes: identifying, via a computer network, a digital event associated with a suspected automated fraud or abuse attack; composing, via one or more computers, a digital activity signature of the suspected automated fraud or abuse attack based on digital activity associated with the suspected automated fraud or abuse attack; computing, via a machine learning model, an encoded representation of the digital activity signature; searching, via the one or more computers, an automated fraud or abuse signature registry based on the encoded representation of the digital activity signature; determining a likely origin of the digital event based on the searching of the automated fraud or abuse signature registry; and selectively implementing one or more automated threat mitigation actions based on the likely origin of the digital event.
    Type: Application
    Filed: September 12, 2023
    Publication date: December 28, 2023
    Inventors: Kostyantyn Gurnov, Wei Liu, Nicholas Benavides, Volha Leusha, Yanqing Bao, Louie Zhang, Irving Chen, Logan Davis, Andy Cai
  • Systems and methods for machine learning-based detection of an automated fraud attack or an automated abuse attack
    Patent number: 11777962
    Abstract: A method for machine learning-based detection of an automated fraud or abuse attack includes: identifying, via a computer network, a digital event associated with a suspected automated fraud or abuse attack; composing, via one or more computers, a digital activity signature of the suspected automated fraud or abuse attack based on digital activity associated with the suspected automated fraud or abuse attack; computing, via a machine learning model, an encoded representation of the digital activity signature; searching, via the one or more computers, an automated fraud or abuse signature registry based on the encoded representation of the digital activity signature; determining a likely origin of the digital event based on the searching of the automated fraud or abuse signature registry; and selectively implementing one or more automated threat mitigation actions based on the likely origin of the digital event.
    Type: Grant
    Filed: December 18, 2022
    Date of Patent: October 3, 2023
    Assignee: Sift Science, Inc.
    Inventors: Kostyantyn Gurnov, Wei Liu, Nicholas Benavides, Volha Leusha, Yanqing Bao, Louie Zhang, Irving Chen, Logan Davis, Andy Cai
  • SYSTEMS AND METHODS FOR MACHINE LEARNING-BASED DETECTION OF AN AUTOMATED FRAUD ATTACK OR AN AUTOMATED ABUSE ATTACK
    Publication number: 20230199006
    Abstract: A method for machine learning-based detection of an automated fraud or abuse attack includes: identifying, via a computer network, a digital event associated with a suspected automated fraud or abuse attack; composing, via one or more computers, a digital activity signature of the suspected automated fraud or abuse attack based on digital activity associated with the suspected automated fraud or abuse attack; computing, via a machine learning model, an encoded representation of the digital activity signature; searching, via the one or more computers, an automated fraud or abuse signature registry based on the encoded representation of the digital activity signature; determining a likely origin of the digital event based on the searching of the automated fraud or abuse signature registry; and selectively implementing one or more automated threat mitigation actions based on the likely origin of the digital event.
    Type: Application
    Filed: December 18, 2022
    Publication date: June 22, 2023
    Inventors: Kostyantyn Gurnov, Wei Liu, Nicholas Benavides, Volha Leusha, Yanqing Bao, Louie Zhang, Irving Chen, Logan Davis, Andy Cai