The Boeing Company

Pape Maguette Sylla

Karim El Defrawy

Hyun Jin Kim

Ryan F Compton

Michael A Warren

Hyun Joo Kim

Byron Nicholas Heersink

Michael Alton Warren

Systems and methods provide for the evaluation of flight controls for an aerial vehicle and define a vehicle dynamics model corresponding to an aerial vehicle. One or more barrier functions are constructed based on the defined vehicle dynamics model, and candidate invariant sets are identified for the defined vehicle dynamics model using the one or more barrier functions. A plurality of flight controls of the aerial vehicle are analyzed using the identified candidate invariant sets and within the analyzed candidate invariant sets, command tracking of the aerial vehicle is confirmed with control commands, using the analyzed plurality of flight controls. Control commands falling outside of the analyzed candidate invariant sets are identified.

Evaluation of air vehicle flight controls

In an example, a non-transitory machine-readable medium has instructions, which, when executed by a processor of a machine, cause the machine to perform operations including: (i) receiving a plurality of network messages transmitted within a communication network, (ii) analyzing the network messages to determine network traffic information, and (iii) determining, based on the network traffic information, a current system context from among a plurality of system contexts. Each system context indicates a respective aggregate status of devices in the communication network. The operations also include (iv) selecting, based on the current system context, a set of filtering rules from among a plurality of sets of filtering rules, (v) applying the selected set of filtering rules to the network messages to determine a subset of network messages that are acceptable for the current system context, and (vi) forwarding each network message of the subset to a destination of the network message.

Systems and methods for context-aware network message filtering

A method and apparatus for discovering a service dependency chain. Service dependencies are discovered. A potential service dependency chain is identified based on at least a portion of the service dependencies. A number of data paths are built for the potential service dependency chain. A chain transfer entropy is computed for the potential service dependency chain based on the number of data paths. A determination is made as to whether the potential service dependency chain is the service dependency chain based on the chain transfer entropy.

Mapping network service dependencies

A method includes obtaining, at a device, packet data descriptive of authorized traffic of a network. The method also includes generating, at the device, rule elements based on the packet data. The method further includes consolidating, at the device, the rule elements based on distance measures associated with the rule elements. The method also includes generating, at the device, firewall filter rules for the network based on the consolidated rule elements.

Firewall filter rules generation

Example methods and systems for mapping network service and/or application dependencies are provided. Some examples may visualize a large, complex network of network services and/or applications (e.g., Internet services and applications) and their dependencies over time. Each service (or application) may be represented as a node and the visualization may present information regarding the relationships among services and/or applications using directed edges (or lines) with varying thickness, colors, and/or line-styles depending on network data.

A method and apparatus for discovering service dependencies. A plurality of connections is identified between nodes in a data network. A set of connection pairs is identified based on the plurality of connections identified. A set of time series is created for the set of connection pairs using monitoring data received from a plurality of sensors monitoring the data network. Service dependencies may be discovered using the set of time series.

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Calabasas, CA, United States of America

Pape Maguette Sylla