Domain-Specific Data Broker Engine for Context-Aware Avionics Filtering
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Solution Overview
Problem
Existing aircraft data gateways lack a mechanism to perform contextual integrity checks, allowing non-certified applications to send data that can inadvertently affect flight missions, despite cybersecurity algorithms protecting against malicious data.
Innovation Solution
Implementing a high integrity domain-specific data broker engine in the aircraft data gateway to filter data requests based on flight context, ensuring only relevant data is sent to avionics by using a failsafe validation engine with a rule base and domain-specific computational logic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data gateway allows data transfer from external applications to avionics, then operational efficiency and safety are improved through real-time updates, but risk of inadvertent effects increases due to lack of contextual integrity checks
Solution Approach 1:
The patent introduces a data broker engine as an intermediary component between external applications and avionics systems. This broker engine receives data requests from external applications, validates them against flight context parameters (such as flight phase, altitude, speed), and selectively forwards only appropriate requests to the avionics. This intermediary layer enables real-time data updates while preventing inadvertent effects by filtering out contextually inappropriate requests.
Solution Approach 2:
The system performs preliminary validation of data requests against flight context before forwarding them to avionics. The data broker engine checks whether incoming requests are appropriate for the current flight state (e.g., preventing flight plan modifications during certain phases, blocking altitude changes that would exceed safe limits). This preliminary action ensures data integrity while maintaining operational efficiency.
2Reliability
If data gateway implements comprehensive data filtering, then data integrity is improved, but system complexity increases due to additional validation mechanisms
Solution Approach 1:
The data broker engine is designed as a universal component that handles multiple types of data requests (flight plan modifications, performance updates, navigation changes) through a single validation framework. It maintains flight context information and applies context-based filtering rules across different data types, reducing overall system complexity compared to having separate validation mechanisms for each data type.
Solution Approach 2:
The system uses parameter-based validation where the data broker engine monitors flight context parameters (flight phase, altitude, speed, position) and dynamically adjusts which data requests are permitted. This parameter-driven approach provides comprehensive data filtering through a relatively simple mechanism that adapts to different flight conditions without requiring complex hard-coded rules for each scenario.
3Reliability
If data gateway blocks requests from non-certified applications, then safety is improved, but adaptability decreases limiting real-time updates
Solution Approach 1:
The data broker engine applies local quality control by validating each incoming data request against the current flight context rather than uniformly blocking all requests from non-certified applications. It allows appropriate requests (e.g., weather updates during cruise, flight plan modifications during certain phases) while blocking inappropriate ones (e.g., critical navigation changes during takeoff). This contextual approach maintains flight safety while preserving adaptability to legitimate real-time updates.
Solution Approach 2:
The system dynamically adjusts which data requests are permitted based on the current flight state. The data broker engine continuously monitors flight context parameters and adapts its filtering behavior accordingly - being more permissive during certain phases and more restrictive during others. This dynamic approach enables flexible acceptance of data from various sources while maintaining safety through context-aware validation.
Data Source
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AI summary
A system to filter a data transfer between an external application and a component of a vehicle, includes: a failsafe validation engine, wherein the failsafe validation engine includes: a rules engine to process a data model from the external application based on one or more rules, a context analyzer to receive context data associated with the vehicle, process the context data as the one or more rules, and send the one or more rules to the rules engine, and a schematic parser to receive the data model from the rules engine and parse the data model based on one or more object models defined for the component of the vehicle; and a controller to control the failsafe validation engine.