Patents by Inventor Ravi Prasad Bulusu

Ravi Prasad Bulusu 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: 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: 11019088
    Abstract: Techniques are described for processing anomalies detected using user-specified rules with anomalies detected using machine-learning based behavioral analysis models to identify threat indicators and security threats to a computer network. In an embodiment, anomalies are detected based on processing event data at a network security system that used rules-based anomaly detection. These rules-based detected anomalies are acquired by a network security system that uses machine-learning based anomaly detection. The rules-based detected anomalies are processed along with machine learning detected anomalies to detect threat indicators or security threats to the computer network. The threat indicators and security threats are output as alerts to the network security system that used rules-based anomaly detection.
    Type: Grant
    Filed: May 28, 2020
    Date of Patent: May 25, 2021
    Assignee: SPLUNK INC.
    Inventors: Robert Winslow Pratt, Ravi Prasad Bulusu
  • 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: 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
  • Publication number: 20200296124
    Abstract: Techniques are described for processing anomalies detected using user-specified rules with anomalies detected using machine-learning based behavioral analysis models to identify threat indicators and security threats to a computer network. In an embodiment, anomalies are detected based on processing event data at a network security system that used rules-based anomaly detection. These rules-based detected anomalies are acquired by a network security system that uses machine-learning based anomaly detection. The rules-based detected anomalies are processed along with machine learning detected anomalies to detect threat indicators or security threats to the computer network. The threat indicators and security threats are output as alerts to the network security system that used rules-based anomaly detection.
    Type: Application
    Filed: May 28, 2020
    Publication date: September 17, 2020
    Inventors: Robert Winslow Pratt, Ravi Prasad Bulusu
  • Patent number: 10673880
    Abstract: Techniques are described for processing anomalies detected using user-specified rules with anomalies detected using machine-learning based behavioral analysis models to identify threat indicators and security threats to a computer network. In an embodiment, anomalies are detected based on processing event data at a network security system that used rules-based anomaly detection. These rules-based detected anomalies are acquired by a network security system that uses machine-learning based anomaly detection. The rules-based detected anomalies are processed along with machine learning detected anomalies to detect threat indicators or security threats to the computer network. The threat indicators and security threats are output as alerts to the network security system that used rules-based anomaly detection.
    Type: Grant
    Filed: September 26, 2016
    Date of Patent: June 2, 2020
    Assignee: SPLUNK INC.
    Inventors: Robert Winslow Pratt, Ravi Prasad Bulusu
  • 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: 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • Patent number: 10116670
    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 27, 2017
    Date of Patent: October 30, 2018
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Publication number: 20180219897
    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: March 20, 2018
    Publication date: August 2, 2018
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Publication number: 20180146000
    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 2, 2018
    Publication date: May 24, 2018
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Publication number: 20180069888
    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 31, 2017
    Publication date: March 8, 2018
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu
  • Patent number: 9900332
    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: June 7, 2017
    Date of Patent: February 20, 2018
    Assignee: SPLUNK INC.
    Inventors: Sudhakar Muddu, Christos Tryfonas, Ravi Prasad Bulusu