Patents by Inventor Iurii Iuzifovich

Iurii Iuzifovich 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).

  • Distinguishing human-driven DNS queries from machine-to-machine DNS queries
    Patent number: 11093844
    Abstract: The present disclosure is related to a computer-implemented method and system for distinguishing human-driven Doman Name System (DNS) queries from Machine-to-Machine (M2M) DNS queries. The method includes receiving a DNS query, which includes a domain name, generating a probability score for the domain name based on one or more predetermined rules, and categorizing the DNS query as a human-driven DNS query or a M2M DNS query based on the probability score.
    Type: Grant
    Filed: November 21, 2018
    Date of Patent: August 17, 2021
    Assignee: Akamai Technologies, Inc.
    Inventors: James Paugh, Paul O'Leary, Robert S. Wilbourn, Thanh Nguyen, Iurii Iuzifovich, Erik D. Fears
  • Analyzing DNS requests for anomaly detection
    Patent number: 10587646
    Abstract: A computer-implemented method for detecting anomalies in DNS requests comprises receiving a plurality of DNS requests generated within a predetermined period. The predetermined period includes a plurality of DNS data fragments. The method further includes receiving a first DNS request and selecting a plurality of second DNS requests from the plurality of DNS requests such that each of the second DNS requests is a subset of the first DNS request. The method also includes calculating a count value for each of the DNS data fragments, where each of the count values represents a number of instances the second DNS requests appear within one of the DNS data fragments. In some embodiments, the count values for each of the DNS data fragments can be normalized. The method further includes determining an anomaly trend, for example, based on determining that at least one of the count values exceeds a predetermined threshold value.
    Type: Grant
    Filed: August 21, 2018
    Date of Patent: March 10, 2020
    Inventors: Ali Fakeri-Tabrizi, Thanh Nguyen, Hongliang Liu, Paul O'Leary, Mikael Kullberg, Iurii Iuzifovich, James Paugh, Robert S. Wilbourn
  • DISTINGUISHING HUMAN-DRIVEN DNS QUERIES FROM MACHINE-TO-MACHINE DNS QUERIES
    Publication number: 20190164071
    Abstract: The present disclosure is related to a computer-implemented method and system for distinguishing human-driven Doman Name System (DNS) queries from Machine-to-Machine (M2M) DNS queries. The method includes receiving a DNS query, which includes a domain name, generating a probability score for the domain name based on one or more predetermined rules, and categorizing the DNS query as a human-driven DNS query or a M2M DNS query based on the probability score.
    Type: Application
    Filed: November 21, 2018
    Publication date: May 30, 2019
    Applicant: Nominum, Inc.
    Inventors: James Paugh, Paul O'Leary, Robert S. Wilbourn, Thanh Nguyen, Iurii Iuzifovich, Erik D. Fears
  • ANALYZING DNS REQUESTS FOR ANOMALY DETECTION
    Publication number: 20190068634
    Abstract: A computer-implemented method for detecting anomalies in DNS requests comprises receiving a plurality of DNS requests generated within a predetermined period. The predetermined period includes a plurality of DNS data fragments. The method further includes receiving a first DNS request and selecting a plurality of second DNS requests from the plurality of DNS requests such that each of the second DNS requests is a subset of the first DNS request. The method also includes calculating a count value for each of the DNS data fragments, where each of the count values represents a number of instances the second DNS requests appear within one of the DNS data fragments. In some embodiments, the count values for each of the DNS data fragments can be normalized. The method further includes determining an anomaly trend, for example, based on determining that at least one of the count values exceeds a predetermined threshold value.
    Type: Application
    Filed: August 21, 2018
    Publication date: February 28, 2019
    Applicant: Nominum Inc.
    Inventors: Ali Fakeri-Tabrizi, Thanh Nguyen, Hongliang Liu, Paul O'Leary, Mikael Kullberg, Iurii Iuzifovich, James Paugh, Robert S. Wilbourn
  • Distinguishing human-driven DNS queries from machine-to-machine DNS queries
    Patent number: 10164989
    Abstract: The present disclosure is related to a computer-implemented method and system for distinguishing human-driven Domain Name System (DNS) queries from Machine-to-Machine (M2M) DNS queries. The method includes receiving a DNS query, which includes a domain name, generating a probability score for the domain name based on one or more predetermined rules, and categorizing the DNS query as a human-driven DNS query or a M2M DNS query based on the probability score.
    Type: Grant
    Filed: December 15, 2015
    Date of Patent: December 25, 2018
    Assignee: Nominum, Inc.
    Inventors: James Paugh, Paul O'Leary, Robert S. Wilbourn, Thanh Nguyen, Iurii Iuzifovich, Erik D. Fears
  • Analyzing DNS requests for anomaly detection
    Patent number: 10084814
    Abstract: A computer-implemented method for detecting anomalies in DNS requests comprises receiving a plurality of DNS requests generated within a predetermined period. The predetermined period includes a plurality of DNS data fragments. The method further includes receiving a first DNS request and selecting a plurality of second DNS requests from the plurality of DNS requests such that each of the second DNS requests is a subset of the first DNS request. The method also includes calculating a count value for each of the DNS data fragments, where each of the count values represents a number of instances the second DNS requests appear within one of the DNS data fragments. In some embodiments, the count values for each of the DNS data fragments can be normalized. The method further includes determining an anomaly trend, for example, based on determining that at least one of the count values exceeds a predetermined threshold value.
    Type: Grant
    Filed: October 31, 2017
    Date of Patent: September 25, 2018
    Assignee: Nominum, Inc.
    Inventors: Ali Fakeri-Tabrizi, Thanh Nguyen, Hongliang Liu, Paul O'Leary, Mikael Kullberg, Iurii Iuzifovich, James Paugh, Robert S. Wilbourn