Patents by Inventor Lizzy Tengana

Lizzy Tengana 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: 11991169
    Abstract: In one approach, a method includes: receiving a reference login event input from a user, the reference login event input being associated with a first session of the user logging into an account; receiving a new login event input from the user, the new login event input being associated with a second session of the user logging into the account; accessing a machine learning model, wherein the machine learning model is trained using data selected based on a similarity of behavior between different users; and authenticating, with the machine learning model, the user for the account, based at least in part on the reference login event input and the new login event input. In examples, the reference and new login event inputs comprise one or more items of biometric data generated by interaction of the user in a web environment and/or a mobile environment for logging into the account.
    Type: Grant
    Filed: January 13, 2021
    Date of Patent: May 21, 2024
    Assignee: EASY SOLUTIONS ENTERPRISES, CORP.
    Inventors: Jesus Alberto Solano Gomez, Martin Ochoa Ronderos, Esteban Rivera Guerrero, Alejandra Castelblanco Cruz, Lizzy Tengana Hurtado, Christian David Lopez Escobar
  • Patent number: 11537693
    Abstract: In one approach, a method includes: receiving a login event input from a user, the login event input being associated with a session of the user logging into an account; accessing a machine learning model; and authenticating, with the machine learning model, the user for the account, based at least in part on the login event input. In examples, the login event input comprises one or more items of biometric data associated with the user, an item of the one or more items of biometric data associated being generated by interaction of the user with an input device for logging into the account, and the interaction communicating a login credential of the user. In examples, an item of the one or more items of biometric data associated with the user is keyboard event-related biometric data, or mouse event-related biometric data.
    Type: Grant
    Filed: February 21, 2020
    Date of Patent: December 27, 2022
    Assignee: EASY SOLUTIONS ENTERPRISES, CORP.
    Inventors: Jesus Solano, Lizzy Tengana, Alejandra Castelblanco, Esteban Rivera, Christian Lopez, Martin Ochoa
  • Publication number: 20220224683
    Abstract: In one approach, a method includes: receiving a reference login event input from a user, the reference login event input being associated with a first session of the user logging into an account; receiving a new login event input from the user, the new login event input being associated with a second session of the user logging into the account; accessing a machine learning model, wherein the machine learning model is trained using data selected based on a similarity of behavior between different users; and authenticating, with the machine learning model, the user for the account, based at least in part on the reference login event input and the new login event input. In examples, the reference and new login event inputs comprise one or more items of biometric data generated by interaction of the user in a web environment and/or a mobile environment for logging into the account.
    Type: Application
    Filed: January 13, 2021
    Publication date: July 14, 2022
    Inventors: Jesus Alberto Solano Gomez, Martin Ochoa Ronderos, Esteban Rivera Guerrero, Alejandra Castelblanco Cruz, Lizzy Tengana Hurtado, Christian David Lopez Escobar
  • Patent number: 11144752
    Abstract: A method for verifying authenticity of a physical document includes receiving an image of a physical document to be authenticated including the physical document and a background. A pre-processed image is produced that includes the physical document separated from the background. The producing includes separating the physical document from the background by semantic segmentation utilizing an artificial neural network trained using an augmented dataset generated by applying geometric transformations over different backgrounds. Features of the pre-processed image are extracted to determine a document type. In response to determining the document type of the physical document, the method includes verifying, utilizing a machine learning classifier, whether the physical document is authentic based on the extracted features relative to expected features for the corresponding document type. An indication of whether the physical document is authentic based on the verifying is generated.
    Type: Grant
    Filed: May 12, 2020
    Date of Patent: October 12, 2021
    Assignee: Cyxtera Cybersecurity, Inc.
    Inventors: Alejandra Castelblanco Cruz, Martin Ochoa Ronderos, Jesus Alberto Solano Gomez, Esteban Rivera Guerrero, Lizzy Tengana Hurtado, Christian David Lopez Escobar
  • Publication number: 20210264003
    Abstract: In one approach, a method includes: receiving a login event input from a user, the login event input being associated with a session of the user logging into an account; accessing a machine learning model; and authenticating, with the machine learning model, the user for the account, based at least in part on the login event input. In examples, the login event input comprises one or more items of biometric data associated with the user, an item of the one or more items of biometric data associated being generated by interaction of the user with an input device for logging into the account, and the interaction communicating a login credential of the user. In examples, an item of the one or more items of biometric data associated with the user is keyboard event-related biometric data, or mouse event-related biometric data.
    Type: Application
    Filed: February 21, 2020
    Publication date: August 26, 2021
    Inventors: Jesus Solano, Lizzy Tengana, Alejandra Castelblanco, Esteban Rivera, Christian Lopez, Martin Ochoa