Patents by Inventor Sudhakar Muddu

Sudhakar Muddu 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).

  • Lateral movement detection for network security analysis
    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
  • PROCESSING ANOMALY DATA TO IDENTIFY THREATS TO NETWORK SECURITY
    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
  • Interactive threat geo-map for monitoring computer network security
    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
  • ANOMALY DETECTION BASED ON COMMUNICATION BETWEEN ENTITIES OVER A NETWORK
    Publication number: 20190327251
    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: July 3, 2019
    Publication date: October 24, 2019
    Inventors: Sudhakar Muddu, Christos Tryfonas, Joseph Auguste Zadeh, Alexander Beebe Bond, Ashwin Athalye
  • Detection of anomalies, threat indicators, and threats to network security
    Patent number: 10419450
    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: September 17, 2019
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • Data retrieval in security anomaly detection platform with shared model state between real-time and batch paths
    Patent number: 10419465
    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: November 6, 2018
    Date of Patent: September 17, 2019
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Event information access interface in data intake stage of a distributed data processing system
    Patent number: 10419462
    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 2, 2018
    Date of Patent: September 17, 2019
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Event specific entity relationship discovery in data intake stage of a distributed data processing system
    Patent number: 10419463
    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: March 20, 2018
    Date of Patent: September 17, 2019
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Malware communications detection
    Patent number: 10389738
    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: August 20, 2019
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Joseph Auguste Zadeh, Alexander Beebe Bond, Ashwin Athalye
  • METHOD AND SYSTEM FOR GENERATING AN ENTITIES VIEW WITH RISK-LEVEL SCORING FOR PERFORMING COMPUTER SECURITY MONITORING
    Publication number: 20190173893
    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 31, 2019
    Publication date: June 6, 2019
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • Interface Providing An Interactive Trendline For A Detected Threat to Facilitate Evaluation For False Positives
    Publication number: 20190158517
    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 28, 2019
    Publication date: May 23, 2019
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • Identity resolution in data intake of a distributed data processing system
    Patent number: 10291635
    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: May 14, 2019
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Method and System for Generating An Interactive Kill Chain View for Training A Machine Learning Model for Identifying Threats
    Publication number: 20190109868
    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: December 10, 2018
    Publication date: April 11, 2019
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • Event views in data intake stage of machine data processing platform
    Patent number: 10243970
    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 26, 2019
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Data Retrieval in Security Anomaly Detection Platform with Shared Model State between Real-Time and Batch Paths
    Publication number: 20190075126
    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: November 6, 2018
    Publication date: March 7, 2019
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Method and system for reviewing identified threats for performing computer security monitoring
    Patent number: 10212174
    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: February 19, 2019
    Assignee: Splunk Inc.
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • Interface providing an interactive timeline for evaluating instances of potential network compromise
    Patent number: 10193901
    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 29, 2019
    Assignee: Splunk Inc.
    Inventors: Sudhakar Muddu, Christos Tryfonas
  • ANOMALY DETECTION BASED ON CONNECTION REQUESTS IN NETWORK TRAFFIC
    Publication number: 20180367551
    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: Application
    Filed: July 31, 2018
    Publication date: December 20, 2018
    Inventors: Sudhakar Muddu, Christos Tryfonas, Marios Iliofotou
  • Sharing model state between real-time and batch paths in network security anomaly detection
    Patent number: 10158652
    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: December 18, 2018
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Method and system for generating a kill chain for monitoring computer network security
    Patent number: 10154047
    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: December 11, 2018
    Assignee: Splunk Inc.
    Inventors: Sudhakar Muddu, Christos Tryfonas