The Future Airborne Capability Environment (FACE®) Standard is an Open Architecture approach to creating reusable, interoperable software for DoD Platforms (https://www.opengroup.org/face). The FACE Consortium was formed in 2010 to define an open avionics environment for all military airborne platform types. Vanderbilt has been an Academia team member supporting the FACE standard development effort since its inception in 2009 assisting in the formative concepts and continues to provide key technical

Modern cyber-physical systems (CPS) are highly complex systems-of-systems, in which understanding the breadth and severity of cyberattacks is highly challenging. As cyberattacks and defensive operations become increasingly automated, there is a greater need to understand the complexities of interactions between the cyber and physical worlds. A scalable, detailed simulation platform will provide a means of developing and evaluating automated techniques within these complex systems.

This project aims to develop a new Science of Design for societal-scale Cyber- Physical Systems (CPS).

This project aims to transition recent research results that automate portions of the verification process of Cyber-Physical Systems into broader practice, particularly with industrial and student users. Cyber-physical systems (CPS) are networked embedded computing systems coupled with physics, such as in motor vehicles, aircraft, medical devices, and the electrical grid.

Cyber-Physical Systems (CPS) are composed of a wide range of networked physical, computational, and human/organization components. These systems are highly complex as they have many different heterogeneous components, such as physical, computational, and human. Simulation-based evaluation of the behavior of CPS is complex, as it involves multiple, heterogeneous, interacting domains. Each simulation domain has sophisticated tools, but their integration into a coherent framework is a difficult, time-consuming, labor-intensive, and error-prone task.

Evaluating the cybersecurity of a complex Industrial Control Systems (ICS), such as the Railway Transportation System (RTS), against a variety of cyber threats is a significantly hard and multi-faceted problem.

Automated design processes, especially using Machine Learning/AI techniques, require proposed systems to be evaluated across all relevant attributes, requirements, and concerns.  Traditionally, teams create models in a set of engineering tools for design evaluation data. 

The goal of this project is to study how domain-specific languages (DSLs) can be used to represent components of legacy systems and to use the DSLs to enhance those components. The project involves formal methods, compilers, and program analysis, such as symbolic execution.