Abstract: Techniques for facilitating advanced avionics functionality in legacy aircrafts are described. In operation, a flight data request is created in a first format for receiving at least avionics data from an avionics system of an aircraft. The flight data request is then converted into a modified flight data request in the second format. The modified fight data request is then communicated to the avionics system. A flight data response is received from the avionics system in response to the modified flight data request, where the flight data response is received in the second format and comprises at least the avionics data. The flight data response is then converted from the second format into the first format. Subsequently, at least the avionics data is utilized during the operation of the aircraft.

Abstract: Techniques for detecting intrusion in computing devices onboard an aircraft are described. In an example, data traffic associated with a computing device onboard an aircraft is monitored, where the data traffic originates from at least one source device coupled to the computing device. The data traffic may then be analyzed using an intruder detection machine learning model to identify an anomalous data pattern. Upon identification of the anomalous data pattern, an anomalous source device from the at least one source device corresponding to the anomalous data pattern may be identified. Subsequently, a notification indicative of a potential security breach associated with the anomalous source device may be generated.

Abstract: Systems, apparatuses, methods, and computer program products are provided herein. For example, a method may include access aviation specification data. In some embodiments, the method may include training a generative machine learning model using aviation specification data. In some embodiments, the method may include generating synthetic aviation data using the generative machine learning model. In some embodiments, the method may include training one or more global positioning system (GPS) spoofing detection machine learning models using the synthetic aviation data and historical aviation operations data. In some embodiments, the method may include deploying a first GPS spoofing detection machine learning model of the one or more GPS spoofing detection machine learning models to an edge-based device.

Abstract: Systems, apparatuses, methods, and computer program products are provided herein. For example, a method may include receiving aviation operations database status data associated with an aviation operations database. In some embodiments, the method may include generating an aviation operations package based on the aviation operations database status data. In some embodiments, the method may include encrypting the aviation operations package using a cloud-based key. In some embodiments, the method may include deploying the aviation operations package to an onboard aviation operations device.

Abstract: Methods and systems for providing platform agnostic flight management data access for a flight management system (FMS) of an aircraft have been developed. First, a configuration file is loaded to a configuration database. The configuration file is for a data format of an external data source from the aircraft. Upon receiving a data access request from a user for external data from the external data source, downloading the configuration file is downloaded to an FMS data formatter. The configuration file is parsed with a data processor component of the FMS data formatter to update a rule set. The FMS data formatter receives an external data file from an application programing interface (API) of the external data source. The external data file is parsed with a rule engine of the FMS data formatter using the updated rule set. A flight plan file is generated with the FMS data formatter using the parsed external data file and sent to the FMS on the aircraft.

Abstract: Methods and systems for providing platform agnostic flight management data access for a flight management system (FMS) of an aircraft have been developed. First, a configuration file is loaded to a configuration database. The configuration file is for a data format of an external data source from the aircraft. Upon receiving a data access request from a user for external data from the external data source, downloading the configuration file is downloaded to an FMS data formatter. The configuration file is parsed with a data processor component of the FMS data formatter to update a rule set. The FMS data formatter receives an external data file from an application programing interface (API) of the external data source. The external data file is parsed with a rule engine of the FMS data formatter using the updated rule set. A flight plan file is generated with the FMS data formatter using the parsed external data file and sent to the FMS on the aircraft.