Abstract: Event correlation may include identifying a feature set for each log file of a plurality of log files, and extracting the feature set for each event of a plurality of events in each log file of the plurality of log files. Event correlation may further include determining a plurality of trace event pairs linkage strength values for an event from a first log file of the plurality of log files and a plurality of events from a second log file of the plurality of log files. The trace event pairs linkage strength values may represent an overlap of the feature set for the event from the first log file and the feature set for each of the plurality of events from the second log file.

Abstract: A method for provisioning a computer includes providing a graph that defines relationships between one or more hardware components of a plurality of computers and component characteristics of the one or more hardware components, and relationships between one or more applications and requirements of the one or more applications. The method further includes receiving a selection of an application and determining, via the graph, whether at least one computer with hardware components capable of meeting the requirements of the application exists. If a computer exits, the method also includes communicating the application to the computer; triggering the computer to execute the application; and communicating, from the computer, data processed by the application to an external system.

Abstract: Contextual graph matching based anomaly detection may include evaluating computer-generated log file data to create a master directed graph that specifies known events and transitions between the known events. The master directed graph may be processed to determine a plurality of decomposed master graph walks. Incoming computer-generated log file data may be evaluated to create an incoming directed graph that specifies unknown events and transitions between the unknown events. The incoming directed graph may be processed to determine a decomposed incoming walk. Overlap, distance difference, and correlation scores may be determined for each walk pair of a plurality of walk pairs including each of the plurality of decomposed master graph walks and the decomposed incoming walk. One of the decomposed master graph walks may be selected based on the overlap score, the difference score, and the correlation score, to detect an anomaly.

Abstract: A method for provisioning a computer includes providing a graph that defines relationships between one or more hardware components of a plurality of computers and component characteristics of the one or more hardware components, and relationships between one or more applications and requirements of the one or more applications. The method further includes receiving a selection of an application and determining, via the graph, whether at least one computer with hardware components capable of meeting the requirements of the application exists. If a computer exits, the method also includes communicating the application to the computer; triggering the computer to execute the application; and communicating, from the computer, data processed by the application to an external system.

Abstract: A method for provisioning a computer includes providing a graph that defines relationships between one or more hardware components of a plurality of computers and component characteristics of the one or more hardware components, and relationships between one or more applications and requirements of the one or more applications. The method further includes receiving a selection of an application and determining, via the graph, whether at least one computer with hardware components capable of meeting the requirements of the application exists. If a computer exits, the method also includes communicating the application to the computer; triggering the computer to execute the application; and communicating, from the computer, data processed by the application to an external system.

Abstract: A method for provisioning a computer includes providing a graph that defines relationships between one or more hardware components of a plurality of computers and component characteristics of the one or more hardware components, and relationships between one or more applications and requirements of the one or more applications. The method further includes receiving a selection of an application and determining, via the graph, whether at least one computer with hardware components capable of meeting the requirements of the application exists. If a computer exits, the method also includes communicating the application to the computer; triggering the computer to execute the application; and communicating, from the computer, data processed by the application to an external system.

Abstract: Event correlation may include identifying a feature set for each log file of a plurality of log files, and extracting the feature set for each event of a plurality of events in each log file of the plurality of log files. Event correlation may further include determining a plurality of trace event pairs linkage strength values for an event from a first log file of the plurality of log files and a plurality of events from a second log file of the plurality of log files. The trace event pairs linkage strength values may represent an overlap of the feature set for the event from the first log file and the feature set for each of the plurality of events from the second log file.

Abstract: Event correlation may include identifying a feature set for each log file of a plurality of log files, and extracting the feature set for each event of a plurality of events in each log file of the plurality of log files. Event correlation may further include determining a plurality of trace event pairs linkage strength values for an event from a first log file of the plurality of log files and a plurality of events from a second log file of the plurality of log files. The trace event pairs linkage strength values may represent an overlap of the feature set for the event from the first log file and the feature set for each of the plurality of events from the second log file.

Abstract: A data lineage tracking system may include a memory storing a module comprising machine readable instructions to obtain trace log entries representing an interaction with, a manipulation of, and/or a creation of a data value. The data lineage tracking system may further include machine readable instructions to select the trace log entries that are associated with commands performed by an application, cluster similar trace log entries from the selected trace log entries, and analyze mappings between the clustered trace log entries to determine data lineage flow associated with the data value.

Abstract: Contextual graph matching based anomaly detection may include evaluating computer-generated log file data to create a master directed graph that specifies known events and transitions between the known events. The master directed graph may be processed to determine a plurality of decomposed master graph walks. Incoming computer-generated log file data may be evaluated to create an incoming directed graph that specifies unknown events and transitions between the unknown events. The incoming directed graph may be processed to determine a decomposed incoming walk. Overlap, distance difference, and correlation scores may be determined for each walk pair of a plurality of walk pairs including each of the plurality of decomposed master graph walks and the decomposed incoming walk. One of the decomposed master graph walks may be selected based on the overlap score, the difference score, and the correlation score, to detect an anomaly.

Abstract: Contextual graph matching based anomaly detection may include evaluating computer-generated log file data to create a master directed graph that specifies known events and transitions between the known events. The master directed graph may be processed to determine a plurality of decomposed master graph walks. Incoming computer-generated log file data may be evaluated to create an incoming directed graph that specifies unknown events and transitions between the unknown events. The incoming directed graph may be processed to determine a decomposed incoming walk. Overlap, distance difference, and correlation scores may be determined for each walk pair of a plurality of walk pairs including each of the plurality of decomposed master graph walks and the decomposed incoming walk. One of the decomposed master graph walks may be selected based on the overlap score, the difference score, and the correlation score, to detect an anomaly.

Abstract: Event correlation may include identifying a feature set for each log file of a plurality of log files, and extracting the feature set for each event of a plurality of events in each log file of the plurality of log files. Event correlation may further include determining a plurality of trace event pairs linkage strength values for an event from a first log file of the plurality of log files and a plurality of events from a second log file of the plurality of log files. The trace event pairs linkage strength values may represent an overlap of the feature set for the event from the first log file and the feature set for each of the plurality of events from the second log file.

Abstract: Contextual graph matching based anomaly detection may include evaluating computer-generated log file data to create a master directed graph that specifies known events and transitions between the known events. The master directed graph may be processed to determine a plurality of decomposed master graph walks. Incoming computer-generated log file data may be evaluated to create an incoming directed graph that specifies unknown events and transitions between the unknown events. The incoming directed graph may be processed to determine a decomposed incoming walk. Overlap, distance difference, and correlation scores may be determined for each walk pair of a plurality of walk pairs including each of the plurality of decomposed master graph walks and the decomposed incoming walk. One of the decomposed master graph walks may be selected based on the overlap score, the difference score, and the correlation score, to detect an anomaly.

Abstract: A data lineage tracking system may include a memory storing a module comprising machine readable instructions to obtain trace log entries representing an interaction with, a manipulation of, and/or a creation of a data value. The data lineage tracking system may further include machine readable instructions to select the trace log entries that are associated with commands performed by an application, cluster similar trace log entries from the selected trace log entries, and analyze mappings between the clustered trace log entries to determine data lineage flow associated with the data value.

Abstract: A scalable and flexible system and method for automatically configuring and re-configuring electronic security interfaces comprising video, audio, wireless hardware and software capable of capturing video and audio designed to be a true “plug-n-play” for an end-user. The system is configured to incorporate almost any type of camera, battery technology, storage device, wifi or cellular technology, microphone and provides access to the web in real-time to add applications, for example, facial recognition web services, real-time comparing of any previously identified and stored object etc. In addition, the system and method is capable of taking inputs of most custom user-deployment application requirement and generating a set of hardware to fulfill a user's particular requirements.