Patents by Inventor Mohammed Ahmad Ababtain

Mohammed Ahmad Ababtain 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).

  • Detection of web application anomalies using machine learning
    Patent number: 11853450
    Abstract: Methods for detection of web application anomalies include receiving, by processors of a web server, web application logs and database logs. A machine learning algorithm is executed by the processors to segment the web application logs and the database logs into clusters based on probability density modeling, such that a variance of features within each cluster is less than a threshold variance. Each cluster corresponds to authorized access of backend databases or unauthorized access of the backend databases. The processors compare each cluster to baseline clusters corresponding to the authorized access of the backend databases. The processors determine that a particular cluster corresponds to the unauthorized access of the backend databases based on the comparison. Responsive to determining that the particular cluster corresponds to the unauthorized access of the backend databases, a display device of the web server generates a graphical user interface representing the particular cluster.
    Type: Grant
    Filed: October 26, 2020
    Date of Patent: December 26, 2023
    Assignee: Saudi Arabian Oil Company
    Inventors: Sultan Saadaldean Alsharif, Mohammed Ahmad Ababtain, Adrian Francis Goodhead
  • Cybersecurity vulnerability classification and remediation based on network utilization
    Patent number: 11277429
    Abstract: A technology solution for remediating a cyberattack risk in a computing resource asset in a network system.
    Type: Grant
    Filed: November 20, 2018
    Date of Patent: March 15, 2022
    Assignee: Saudi Arabian Oil Company
    Inventors: Mohammed Ahmad Ababtain, Sultan Saadaldean Alsharif
  • DETECTION OF WEB APPLICATION ANOMALIES USING MACHINE LEARNING
    Publication number: 20210133346
    Abstract: Methods for detection of web application anomalies include receiving, by processors of a web server, web application logs and database logs. A machine learning algorithm is executed by the processors to segment the web application logs and the database logs into clusters based on probability density modeling, such that a variance of features within each cluster is less than a threshold variance. Each cluster corresponds to authorized access of backend databases or unauthorized access of the backend databases. The processors compare each cluster to baseline clusters corresponding to the authorized access of the backend databases. The processors determine that a particular cluster corresponds to the unauthorized access of the backend databases based on the comparison. Responsive to determining that the particular cluster corresponds to the unauthorized access of the backend databases, a display device of the web server generates a graphical user interface representing the particular cluster.
    Type: Application
    Filed: October 26, 2020
    Publication date: May 6, 2021
    Inventors: Sultan Saadaldean Alsharif, Mohammed Ahmad Ababtain, Adrian Francis Goodhead
  • CYBERSECURITY VULNERABILITY CLASSIFICATION AND REMEDIATION BASED ON NETWORK UTILIZATION
    Publication number: 20200162498
    Abstract: A technology solution for remediating a cyberattack risk in a computing resource asset in a network system.
    Type: Application
    Filed: November 20, 2018
    Publication date: May 21, 2020
    Inventors: Mohammed Ahmad Ababtain, Sultan Saadaldean Alsharif