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).

  • Network Security System with Real-Time and Batch Paths
    Publication number: 20170272458
    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: June 7, 2017
    Publication date: September 21, 2017
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • MODEL TRAINING AND DEPLOYMENT IN COMPLEX EVENT PROCESSING OF COMPUTER NETWORK DATA
    Publication number: 20170223036
    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: April 18, 2017
    Publication date: August 3, 2017
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • Network security system
    Patent number: 9699205
    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 31, 2015
    Date of Patent: July 4, 2017
    Assignee: Splunk Inc.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Complex event processing of computer network data
    Patent number: 9667641
    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: May 30, 2017
    Assignee: Splunk Inc.
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • EVENT SPECIFIC RELATIONSHIP GRAPH GENERATION AND APPLICATION IN A MACHINE DATA PROCESSING PLATFORM
    Publication number: 20170142140
    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: January 27, 2017
    Publication date: May 18, 2017
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Network Security Threat Detection by User/User-Entity Behavioral Analysis
    Publication number: 20170134415
    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: January 23, 2017
    Publication date: May 11, 2017
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • Dual-Path Distributed Architecture for Network Security Analysis
    Publication number: 20170134410
    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: January 25, 2017
    Publication date: May 11, 2017
    Inventors: SUDHAKAR MUDDU, CHRISTOS TRYFONAS, RAVI PRASAD BULUSU
  • Interface having selectable, interactive views for evaluating potential network compromise
    Patent number: 9609011
    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: March 28, 2017
    Assignee: Splunk Inc.
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • Network security threat detection by user/user-entity behavioral analysis
    Patent number: 9609009
    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 26, 2016
    Date of Patent: March 28, 2017
    Assignee: Splunk Inc.
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • Event mini-graphs in data intake stage of machine data processing platform
    Patent number: 9596254
    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: March 14, 2017
    Assignee: Splunk Inc.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Dual-path distributed architecture for network security analysis
    Patent number: 9591010
    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: March 7, 2017
    Assignee: Splunk Inc.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Method And System For Generating A Kill Chain For Monitoring Computer Network Security
    Publication number: 20170063898
    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: October 30, 2015
    Publication date: March 2, 2017
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • Method And System For Reviewing Identified Threats For Performing Computer Security Monitoring
    Publication number: 20170063901
    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: October 30, 2015
    Publication date: March 2, 2017
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • MODULAR MODEL WORKFLOW IN A DISTRIBUTED COMPUTATION SYSTEM
    Publication number: 20170063886
    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: October 30, 2015
    Publication date: March 2, 2017
    Inventors: Sudhakar Muddu, Christos Tryfonas, Sathyanarayanan Kavacheri
  • PROBABILISTIC SUFFIX TREES FOR NETWORK SECURITY ANALYSIS
    Publication number: 20170063887
    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: October 30, 2015
    Publication date: March 2, 2017
    Inventors: Sudhakar Muddu, Christos Tryfonas, Marios Iliofotou
  • COMPLEX EVENT PROCESSING OF COMPUTER NETWORK DATA
    Publication number: 20170063906
    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: October 30, 2015
    Publication date: March 2, 2017
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • Network Security Threat Detection by User/User-Entity Behavioral Analysis
    Publication number: 20170063894
    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: October 26, 2016
    Publication date: March 2, 2017
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • MACHINE-GENERATED TRAFFIC DETECTION (BEACONING)
    Publication number: 20170063889
    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: October 30, 2015
    Publication date: March 2, 2017
    Inventors: Sudhakar Muddu, Christos Tryfonas, Marios Iliofotou
  • IDENTITY RESOLUTION IN DATA INTAKE STAGE OF MACHINE DATA PROCESSING PLATFORM
    Publication number: 20170063904
    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: October 30, 2015
    Publication date: March 2, 2017
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • MALWARE COMMUNICATIONS DETECTION
    Publication number: 20170063888
    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: October 30, 2015
    Publication date: March 2, 2017
    Inventors: Sudhakar Muddu, Christos Tryfonas, Joseph Auguste Zadeh, Alexander Beebe Bond, Ashwin Athalye