Patents by Inventor Robin Lynn Burkett
Robin Lynn Burkett 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).
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Patent number: 11522882Abstract: Implementations are directed to methods for detecting and identifying advanced persistent threats (APTs) in networks, including receiving first domain activity data from a first network domain and second domain activity data from a second network domain, including multiple alerts from the respective first and second network domains and where each alert of the multiple alerts results from one or more detected events in the respective first or second network domains. A classification determined for each alert of the multiple alerts with respect to a cyber kill chain. A dependency is then determined for each of one or more pairs of alerts and a graphical visualization of the multiple alerts is generated, where the graphical visualization includes multiple nodes and edges between the nodes, each node corresponding to the cyber kill chain and representing at least one alert, and each edge representing a dependency between alerts.Type: GrantFiled: October 19, 2020Date of Patent: December 6, 2022Assignee: Accenture Global Solutions LimitedInventors: Amin Hassanzadeh, Azzedine Benameur, Robin Lynn Burkett, Apoorv Krishak, Chien An Chen, Nahid Farhady Ghalaty
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Patent number: 11323460Abstract: Malicious threat detection through time-series graph analysis, in which a data analysis device receives a data file comprising multiple log data entries. The log data entries include parameters associated with a computer network event in a computing network. The data analysis device produces a graphical model of the computing network based on at least one parameter included in the log data. The data analysis device also identifies a parameter associated with a node of the computer network represented by the graphical model, and performs a time-series analysis on the parameter. The data analysis device further determines, based on the time-series analysis on the parameter, at least one of an anomalous event associated with the computing network or a malicious event associated with the computing network.Type: GrantFiled: October 30, 2019Date of Patent: May 3, 2022Assignee: Accenture Global Solutions LimitedInventors: Louis William DiValentin, Joshua Patterson, Keith Kraus, Robin Lynn Burkett, Michael Evan Wendt
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Patent number: 11212306Abstract: Graph database analysis for network anomaly detection systems, in which a data analysis device receives multiple log data entries including parameters associated with a computer network event in a computing network. The data analysis device extracts one or more parameters in real-time and generates a network event graph based on at least one of a first graph metric or a second graph metric. The first and second graph metrics are based on the one or more extracted parameters. The data analysis device detects, based on queries performed on the network event graph, at least one of an anomalous event associated with the computing network or a malicious event associated with the computing network.Type: GrantFiled: December 23, 2019Date of Patent: December 28, 2021Assignee: Accenture Global Solutions LimitedInventors: Joshua Patterson, Michael Evan Wendt, Keith Kraus, Louis William DiValentin, Robin Lynn Burkett
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Publication number: 20210037029Abstract: Implementations are directed to methods for detecting and identifying advanced persistent threats (APTs) in networks, including receiving first domain activity data from a first network domain and second domain activity data from a second network domain, including multiple alerts from the respective first and second network domains and where each alert of the multiple alerts results from one or more detected events in the respective first or second network domains. A classification determined for each alert of the multiple alerts with respect to a cyber kill chain. A dependency is then determined for each of one or more pairs of alerts and a graphical visualization of the multiple alerts is generated, where the graphical visualization includes multiple nodes and edges between the nodes, each node corresponding to the cyber kill chain and representing at least one alert, and each edge representing a dependency between alerts.Type: ApplicationFiled: October 19, 2020Publication date: February 4, 2021Inventors: Amin Hassanzadeh, Azzedine Benameur, Robin Lynn Burkett, Apoorv Krishak, Chien An Chen, Nahid Farhady Ghalaty
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Patent number: 10812499Abstract: Implementations are directed to methods for detecting and identifying advanced persistent threats (APTs) in networks, including receiving first domain activity data from a first network domain and second domain activity data from a second network domain, including multiple alerts from the respective first and second network domains and where each alert of the multiple alerts results from one or more detected events in the respective first or second network domains. A classification determined for each alert of the multiple alerts with respect to a cyber kill chain. A dependency is then determined for each of one or more pairs of alerts and a graphical visualization of the multiple alerts is generated, where the graphical visualization includes multiple nodes and edges between the nodes, each node corresponding to the cyber kill chain and representing at least one alert, and each edge representing a dependency between alerts.Type: GrantFiled: November 9, 2017Date of Patent: October 20, 2020Assignee: Accenture Global Solutions LimitedInventors: Amin Hassanzadeh, Azzedine Benameur, Robin Lynn Burkett, Apoorv Krishak, Chien An Chen, Nahid Farhady Ghalaty
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Publication number: 20200145441Abstract: Graph database analysis for network anomaly detection systems, in which a data analysis device receives multiple log data entries including parameters associated with a computer network event in a computing network. The data analysis device extracts one or more parameters in real-time and generates a network event graph based on at least one of a first graph metric or a second graph metric. The first and second graph metrics are based on the one or more extracted parameters. The data analysis device detects, based on queries performed on the network event graph, at least one of an anomalous event associated with the computing network or a malicious event associated with the computing network.Type: ApplicationFiled: December 23, 2019Publication date: May 7, 2020Inventors: Joshua Patterson, Michael Evan Wendt, Keith Kraus, Louis William DiValentin, Robin Lynn Burkett
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Publication number: 20200076836Abstract: Malicious threat detection through time-series graph analysis, in which a data analysis device receives a data file comprising multiple log data entries. The log data entries include parameters associated with a computer network event in a computing network. The data analysis device produces a graphical model of the computing network based on at least one parameter included in the log data. The data analysis device also identifies a parameter associated with a node of the computer network represented by the graphical model, and performs a time-series analysis on the parameter. The data analysis device further determines, based on the time-series analysis on the parameter, at least one of an anomalous event associated with the computing network or a malicious event associated with the computing network.Type: ApplicationFiled: October 30, 2019Publication date: March 5, 2020Inventors: Louis William DiValentin, Joshua Patterson, Keith Kraus, Robin Lynn Burkett, Michael Evan Wendt
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Patent number: 10530796Abstract: Graph database analysis for network anomaly detection systems, in which a data analysis device receives multiple log data entries including parameters associated with a computer network event in a computing network. The data analysis device extracts one or more parameters in real-time and generates a network event graph based on at least one of a first graph metric or a second graph metric. The first and second graph metrics are based on the one or more extracted parameters. The data analysis device detects, based on queries performed on the network event graph, at least one of an anomalous event associated with the computing network or a malicious event associated with the computing network.Type: GrantFiled: September 6, 2017Date of Patent: January 7, 2020Assignee: Accenture Global Solutions LimitedInventors: Joshua Patterson, Michael Evan Wendt, Keith Kraus, Louis William DiValentin, Robin Lynn Burkett
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Patent number: 10476896Abstract: Malicious threat detection through time-series graph analysis, in which a data analysis device receives a data file comprising multiple log data entries. The log data entries include parameters associated with a computer network event in a computing network. The data analysis device produces a graphical model of the computing network based on at least one parameter included in the log data. The data analysis device also identifies a parameter associated with a node of the computer network represented by the graphical model, and performs a time-series analysis on the parameter. The data analysis device further determines, based on the time-series analysis on the parameter, at least one of an anomalous event associated with the computing network or a malicious event associated with the computing network.Type: GrantFiled: September 13, 2016Date of Patent: November 12, 2019Assignee: Accenture Global Solutions LimitedInventors: Louis William DiValentin, Joshua Patterson, Keith Kraus, Robin Lynn Burkett, Michael Evan Wendt
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Publication number: 20190141058Abstract: Implementations are directed to methods for detecting and identifying advanced persistent threats (APTs) in networks, including receiving first domain activity data from a first network domain and second domain activity data from a second network domain, including multiple alerts from the respective first and second network domains and where each alert of the multiple alerts results from one or more detected events in the respective first or second network domains. A classification determined for each alert of the multiple alerts with respect to a cyber kill chain. A dependency is then determined for each of one or more pairs of alerts and a graphical visualization of the multiple alerts is generated, where the graphical visualization includes multiple nodes and edges between the nodes, each node corresponding to the cyber kill chain and representing at least one alert, and each edge representing a dependency between alerts.Type: ApplicationFiled: November 9, 2017Publication date: May 9, 2019Inventors: Amin Hassanzadeh, Azzedine Benameur, Robin Lynn Burkett, Apoorv Krishak, Chien An Chen, Nahid Farhady Ghalaty
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Publication number: 20180077175Abstract: Malicious threat detection through time-series graph analysis, in which a data analysis device receives a data file comprising multiple log data entries. The log data entries include parameters associated with a computer network event in a computing network. The data analysis device produces a graphical model of the computing network based on at least one parameter included in the log data. The data analysis device also identifies a parameter associated with a node of the computer network represented by the graphical model, and performs a time-series analysis on the parameter. The data analysis device further determines, based on the time-series analysis on the parameter, at least one of an anomalous event associated with the computing network or a malicious event associated with the computing network.Type: ApplicationFiled: September 13, 2016Publication date: March 15, 2018Inventors: Louis William DiValentin, Joshua Patterson, Keith Kraus, Robin Lynn Burkett, Michael Evan Wendt
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Publication number: 20180069885Abstract: Graph database analysis for network anomaly detection systems, in which a data analysis device receives multiple log data entries including parameters associated with a computer network event in a computing network. The data analysis device extracts one or more parameters in real-time and generates a network event graph based on at least one of a first graph metric or a second graph metric. The first and second graph metrics are based on the one or more extracted parameters. The data analysis device detects, based on queries performed on the network event graph, at least one of an anomalous event associated with the computing network or a malicious event associated with the computing network.Type: ApplicationFiled: September 6, 2017Publication date: March 8, 2018Inventors: Joshua Patterson, Michael Evan Wendt, Keith Kraus, Louis William DiValentin, Robin Lynn Burkett
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Patent number: 9886582Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining threat data contextualization.Type: GrantFiled: August 31, 2015Date of Patent: February 6, 2018Assignee: Accenture Global Sevices LimitedInventors: Elvis Hovor, David William Rozmiarek, Robin Lynn Burkett, Matthew Carver, Mohamed H. El-Sharkawi
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Publication number: 20170061132Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining threat data contextualization.Type: ApplicationFiled: August 31, 2015Publication date: March 2, 2017Inventors: Elvis Hovor, David William Rozmiarek, Robin Lynn Burkett, Matthew Carver, Mohamed H. El-Sharkawi