Patents by Inventor Matt Swann

Matt Swann 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: 9825978
    Abstract: Lateral movement detection may be performed by employing different detection models to score logon sessions. The different detection models may be implemented by and/or utilize counts computed from historical security event data. The different detection models may include probabilistic intrusion detection models for detecting compromised behavior based on logon behavior, a sequence of security events observed during a logon session, inter-event time between security events observed during a logon session, and/or an attempt to logon using explicit credentials. Scores for each logon session that are output by the different detection models may be combined to generate a ranking score for each logon session. A list of ranked alerts may be generated based on the ranking score for each logon session to identify compromised authorized accounts and/or compromised machines. An attack graph may be automatically generated based on compromised account-machine pairs to visually display probable paths of an attacker.
    Type: Grant
    Filed: January 16, 2017
    Date of Patent: November 21, 2017
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Ram Shankar Siva Kumar, Nguyen Song Khanh Vu, Marco DiPlacido, Vinod Nair, Aniruddha Das, Matt Swann, Keerthi Selvaraj, Sundararajan Sellamanickam
  • Publication number: 20170126717
    Abstract: Lateral movement detection may be performed by employing different detection models to score logon sessions. The different detection models may be implemented by and/or utilize counts computed from historical security event data. The different detection models may include probabilistic intrusion detection models for detecting compromised behavior based on logon behavior, a sequence of security events observed during a logon session, inter-event time between security events observed during a logon session, and/or an attempt to logon using explicit credentials. Scores for each logon session that are output by the different detection models may be combined to generate a ranking score for each logon session. A list of ranked alerts may be generated based on the ranking score for each logon session to identify compromised authorized accounts and/or compromised machines. An attack graph may be automatically generated based on compromised account-machine pairs to visually display probable paths of an attacker.
    Type: Application
    Filed: January 16, 2017
    Publication date: May 4, 2017
    Inventors: Ram Shankar Siva Kumar, Nguyen Song Khanh Vu, Marco DiPlacido, Vinod Nair, Aniruddha Das, Matt Swann, Keerthi Selvaraj, Sundararajan Sellamanickam
  • Patent number: 9591006
    Abstract: Lateral movement detection may be performed by employing different detection models to score logon sessions. The different detection models may be implemented by and/or utilize counts computed from historical security event data. The different detection models may include probabilistic intrusion detection models for detecting compromised behavior based on logon behavior, a sequence of security events observed during a logon session, inter-event time between security events observed during a logon session, and/or an attempt to logon using explicit credentials. Scores for each logon session that are output by the different detection models may be combined to generate a ranking score for each logon session. A list of ranked alerts may be generated based on the ranking score for each logon session to identify compromised authorized accounts and/or compromised machines. An attack graph may be automatically generated based on compromised account-machine pairs to visually display probable paths of an attacker.
    Type: Grant
    Filed: September 18, 2014
    Date of Patent: March 7, 2017
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Ram Shankar Siva Kumar, Nguyen Song Khanh Vu, Marco DiPlacido, Vinod Nair, Aniruddha Das, Matt Swann, Keerthi Selvaraj, Sundararajan Sellamanickam
  • Publication number: 20160088000
    Abstract: Lateral movement detection may be performed by employing different detection models to score logon sessions. The different detection models may be implemented by and/or utilize counts computed from historical security event data. The different detection models may include probabilistic intrusion detection models for detecting compromised behavior based on logon behavior, a sequence of security events observed during a logon session, inter-event time between security events observed during a logon session, and/or an attempt to logon using explicit credentials. Scores for each logon session that are output by the different detection models may be combined to generate a ranking score for each logon session. A list of ranked alerts may be generated based on the ranking score for each logon session to identify compromised authorized accounts and/or compromised machines. An attack graph may be automatically generated based on compromised account-machine pairs to visually display probable paths of an attacker.
    Type: Application
    Filed: September 18, 2014
    Publication date: March 24, 2016
    Inventors: Ram Shankar Siva Kumar, Nguyen Song Khanh Vu, Marco DiPlacido, Vinod Nair, Aniruddha Das, Matt Swann, Keerthi Selvaraj, Sundararajan Sellamanickam