Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for analyzing threat intelligence information. One of the methods includes receiving by a threat information server, threat intelligence information from one or more intelligence feeds and generating one or more identified security threats, identifying a compromise by a management process orchestration server and retrieving information from the threat information server and identifying one or more actions to be performed, determining by an indicator analytics processor, a composite credibility based on the actions, and determining one or more components for profiling and determining indicators of compromise for each component, and communicating the indicators of compromise to the management process orchestration server.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for identifying network security risks. One of the methods includes receiving organizational hierarchy data and receiving access privilege data for a network, generating an adjacency matrix that represents connections between individuals within the organizational hierarchy and various groups, and that represents connections between the individuals and various access privileges, selecting an analytic technique for analyzing the adjacency matrix, determining, for each individual, an individual score that represents a security risk associated with the individual's network account, and in response to determining that the individual score meets a threshold, applying security controls.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for implementing a response to one or more security incidents in a computing network. One of the methods includes identifying a security incident based on detecting one or more indicators of compromise associated with the security incident, comparing the security incident with a predefined ontology that maps the security incident to one or more courses of action, selecting a response strategy that includes one or more of the courses of action, and implementing the response strategy as an automated response.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining network related anomaly scores. One of the methods includes generating a network map including at least a plurality of network nodes and a plurality of edges that indicate communications paths between the plurality of network nodes, obtaining first data indicating network activity over the edges and between the plurality of network nodes for a first time period, generating a model of expected network activity over the edges and between the plurality of network nodes for a future time period using the network map and the first data, obtaining second data indicating network activity over the edges and between the plurality of network nodes for a second time period, and determining an anomaly score using a comparison between the second data and the model of expected network activity.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for analyzing threat intelligence information. One of the methods includes receiving by a threat information server, threat intelligence information from one or more intelligence feeds and generating one or more identified security threats, identifying a compromise by a management process orchestration server and retrieving information from the threat information server and identifying one or more actions to be performed, determining by an indicator analytics processor, a composite credibility based on the actions, and determining one or more components for profiling and determining indicators of compromise for each component, and communicating the indicators of compromise to the management process orchestration server.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining network related anomaly scores. One of the methods includes generating a network map including at least a plurality of network nodes and a plurality of edges that indicate communications paths between the plurality of network nodes, obtaining first data indicating network activity over the edges and between the plurality of network nodes for a first time period, generating a model of expected network activity over the edges and between the plurality of network nodes for a future time period using the network map and the first data, obtaining second data indicating network activity over the edges and between the plurality of network nodes for a second time period, and determining an anomaly score using a comparison between the second data and the model of expected network activity.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining network related anomaly scores. One of the methods includes generating a network map including at least a plurality of network nodes and a plurality of edges that indicate communications paths between the plurality of network nodes, obtaining first data indicating network activity over the edges and between the plurality of network nodes for a first time period, generating a model of expected network activity over the edges and between the plurality of network nodes for a future time period using the network map and the first data, obtaining second data indicating network activity over the edges and between the plurality of network nodes for a second time period, and determining an anomaly score using a comparison between the second data and the model of expected network activity.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining network related anomaly scores. One of the methods includes generating a network map including at least a plurality of network nodes and a plurality of edges that indicate communications paths between the plurality of network nodes, obtaining first data indicating network activity over the edges and between the plurality of network nodes for a first time period, generating a model of expected network activity over the edges and between the plurality of network nodes for a future time period using the network map and the first data, obtaining second data indicating network activity over the edges and between the plurality of network nodes for a second time period, and determining an anomaly score using a comparison between the second data and the model of expected network activity.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for implementing a response to one or more security incidents in a computing network. One of the methods includes identifying a security incident based on detecting one or more indicators of compromise associated with the security incident, comparing the security incident with a predefined ontology that maps the security incident to one or more courses of action, selecting a response strategy that includes one or more of the courses of action, and implementing the response strategy as an automated response.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for analyzing threat intelligence information. One of the methods includes receiving by a threat information server, threat intelligence information from one or more intelligence feeds and generating one or more identified security threats, identifying a compromise by a management process orchestration server and retrieving information from the threat information server and identifying one or more actions to be performed, determining by an indicator analytics processor, a composite credibility based on the actions, and determining one or more components for profiling and determining indicators of compromise for each component, and communicating the indicators of compromise to the management process orchestration server.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for implementing a response to one or more security incidents in a computing network. One of the methods includes identifying a security incident based on detecting one or more indicators of compromise associated with the security incident, comparing the security incident with a predefined ontology that maps the security incident to one or more courses of action, selecting a response strategy that includes one or more of the courses of action, and implementing the response strategy as an automated response.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for implementing a response to one or more security incidents in a computing network. One of the methods includes identifying a security incident based on detecting one or more indicators of compromise associated with the security incident, comparing the security incident with a predefined ontology that maps the security incident to one or more courses of action, selecting a response strategy that includes one or more of the courses of action, and implementing the response strategy as an automated response.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining network related anomaly scores. One of the methods includes generating a network map including at least a plurality of network nodes and a plurality of edges that indicate communications paths between the plurality of network nodes, obtaining first data indicating network activity over the edges and between the plurality of network nodes for a first time period, generating a model of expected network activity over the edges and between the plurality of network nodes for a future time period using the network map and the first data, obtaining second data indicating network activity over the edges and between the plurality of network nodes for a second time period, and determining an anomaly score using a comparison between the second data and the model of expected network activity.