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In the past, aircraft network design did not demand for information security considerations. The aircraft systems were simple, obscure, proprietary and, most importantly for security, the systems have been either physically isolated or they have been connected by directed communication links. The union of the aircraft systems thus formed a federated network. These properties are in sharp contrast with today’s system designs, which rest upon platform-based solutions with shared resources being interconnected by a massively meshed and shared communication network. The resulting connectivity and the high number of interfaces require an in-depth security analysis as the systems also provide functions that are required for the safe operation of the aircraft. This network design evolution, however, resulted in an iterative and continuous adaption of existing network solutions as these have not been developed from scratch.

For an “end-to-end passenger experience that is secure, seamless and efficient” the International Air Transport Association (IATA) proposes Near Field Communication (NFC) and a single token concept to be enablers for future digital travel. NFC is a wireless technology commonly utilized in Portable Electronic Devices (PEDs) and contactless smart cards. It is characterized by the following two attributes: a tangible user interface and secured short range communication. While manufacturers are currently adapting PED settings to enable NFC in the flight mode, the integration and use of this technology in aircraft cabins still remains a challenge. There are no explicit qualification guidelines for electromagnetic compatibility (EMC) testing in an aircraft environment available and there is a lack of a detailed characterization of NFC equipped PEDs.

Aircraft cabin operations shift towards data-driven processes. Cabin-wide multi-system communication networks are introduced to share required data for corresponding novel data-driven applications. Examples are data-driven predictive maintenance applications to reduce the downtime of systems and increase the period of scheduled maintenance or video analytics usage to detect a strained or unruly atmosphere amongst passengers. These applications require a network to transport the associated data and resources for actual computation. Costs and weight have always been the most important factors deciding if new services are introduced within the aircraft cabin. Thus, re-using hardware with free computation capacity that is already installed in the aircraft cabin can target both aspects, weight and costs. Examples for such hardware resources could be the In-flight Entertainment (IFE) equipment being installed in every seat.

Current communication architectures in the aircraft cabin are mostly proprietary and limited to the boundaries of the diverging systems, i.e. existing cabin systems operate mostly isolated from each other. Modern system design, however, requires a shared communication platform in order to enable novel services by means of a contract-based data and information exchange. Data-driven predictive maintenance applications are one example for which the fundamentals are studied intensively, but its integration into a multi-system environment with respect to communication requirements is often neglected. As the aircraft cabin is a highly dynamic environment with changing air pressure, humidity, temperature, and flight attitude, context information is needed in order to get meaningful predictions for e.g. the Remaining Useful Life (RUL) of a system, component or item.

The integration of fuel cell systems as an independent energy source (Auxiliary Power Unit, APU) requires enhanced aircraft cooling architectures. New environmental control systems and systems with an increased cooling demand are investigated in various research projects. Cooling system architectures can be designed which benefit from similar requirements, e.g. by using the same cooling loops. Additionally, an increased cooling demand makes the investigation of alternative heat sinks necessary. For detailed system investigations simulation studies are used. A model library has been created in Dymola/Modelica containing the necessary component models to simulate cooling systems. The used modeling approaches and main model information are presented in this article. In order to understand the basic system behavior a Design of Experiment (DOE) is useful. If only two or three parameters are considered, simulation studies can be performed for each possible parameter combination.

Aircraft are high value-adding and long-living assets, while aircraft cabins are expensive consumer products tailored to each customer. Vastly changing requirements and needs force aircraft holders regularly to instruct modifications in order to remain attractive on the market. Adaptations, modifications, and development of innovations are handled by multiple organizations, not by a central one like the aircraft’s manufacturer or owner. Although the Continuing Airworthiness Management Organization manages all aircraft instance-specific documents as required by aviation regulations, their format and types of management differ. Besides, not all information that arises during a parts design phase is included. That means, overall, the consistent model-based maintenance of data within all phases of PLM up to disposal is not guaranteed.

The increasing functionality associated with the rising complexity of aircraft cabin systems which are used by cabin crew, passengers, maintenance staff and other stakeholders, requires a reconsideration of the methods for the development of aircraft cabin systems. This paper deals with a model-based security engineering approach based on the so called Three-V-Model as an appropriate process model, which represents the governing system engineering process (SEP) associated with the safety engineering process (SafEP) and the security engineering process (SecEP). All three processes are pursued concurrently and are interacting reciprocally by working within the same system model on each development level. We describe in detail the involved model-based security engineering activities of the SecEP and the integration of the CORAS risk analysis method in a consistent System Modeling Language (SysML) approach.