Patents by Inventor Christos Tryfonas

Christos Tryfonas 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: 11411966
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected or threat, and to take action promptly.
    Type: Grant
    Filed: July 19, 2019
    Date of Patent: August 9, 2022
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • Patent number: 11258807
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.
    Type: Grant
    Filed: July 3, 2019
    Date of Patent: February 22, 2022
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Joseph Auguste Zadeh, Alexander Beebe Bond, Ashwin Athalye
  • Patent number: 11146574
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.
    Type: Grant
    Filed: August 5, 2019
    Date of Patent: October 12, 2021
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Patent number: 10986106
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.
    Type: Grant
    Filed: January 31, 2019
    Date of Patent: April 20, 2021
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • Patent number: 10911468
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.
    Type: Grant
    Filed: August 21, 2019
    Date of Patent: February 2, 2021
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Patent number: 10911470
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.
    Type: Grant
    Filed: September 24, 2019
    Date of Patent: February 2, 2021
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Fumei Lam, Georgios Apostolopoulos
  • Patent number: 10904270
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.
    Type: Grant
    Filed: October 30, 2015
    Date of Patent: January 26, 2021
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu, Marios Iliofotou
  • Patent number: 10798113
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.
    Type: Grant
    Filed: September 11, 2019
    Date of Patent: October 6, 2020
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • Patent number: 10778703
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.
    Type: Grant
    Filed: December 10, 2018
    Date of Patent: September 15, 2020
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • Patent number: 10666668
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.
    Type: Grant
    Filed: January 28, 2019
    Date of Patent: May 26, 2020
    Assignee: Splunk Inc.
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • Patent number: 10587633
    Abstract: The disclosed embodiments include a method performed by a computer system. The method includes forming groups of traffic, where each group includes a subset of detected connection requests. The method further includes determining a periodicity of connection requests for each group, identifying a particular group based on whether the periodicity of connection requests of the particular group satisfies a periodicity criterion, determining a frequency of the particular group in the traffic, and identifying the particular group as an anomaly based on whether the frequency of the particular group satisfies a frequency criterion.
    Type: Grant
    Filed: July 31, 2018
    Date of Patent: March 10, 2020
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Marios Iliofotou
  • Patent number: 10581881
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.
    Type: Grant
    Filed: October 31, 2017
    Date of Patent: March 3, 2020
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Sathyanarayanan Kavacheri
  • Patent number: 10560468
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.
    Type: Grant
    Filed: July 20, 2018
    Date of Patent: February 11, 2020
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Marios Iliofotou
  • Publication number: 20200021607
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.
    Type: Application
    Filed: September 24, 2019
    Publication date: January 16, 2020
    Inventors: Sudhakar Muddu, Christos Tryfonas, Fumei Lam, Georgios Apostolopoulos
  • Publication number: 20200007561
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.
    Type: Application
    Filed: September 11, 2019
    Publication date: January 2, 2020
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • Publication number: 20190387007
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.
    Type: Application
    Filed: August 21, 2019
    Publication date: December 19, 2019
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Publication number: 20190364060
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.
    Type: Application
    Filed: August 5, 2019
    Publication date: November 28, 2019
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Patent number: 10476898
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.
    Type: Grant
    Filed: May 31, 2018
    Date of Patent: November 12, 2019
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Fumei Lam, Georgios Apostolopoulos
  • Publication number: 20190342311
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected or threat, and to take action promptly.
    Type: Application
    Filed: July 19, 2019
    Publication date: November 7, 2019
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • Patent number: 10469508
    Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.
    Type: Grant
    Filed: October 30, 2015
    Date of Patent: November 5, 2019
    Assignee: Splunk Inc.
    Inventors: Sudhakar Muddu, Christos Tryfonas