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.

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.

Cyber-physical systems (CPS) are engineered systems created as networks of interacting physical and computational processes. Most modern products in major industrial sectors, such as automotive, avionics, medical devices, and power systems already are or rapidly becoming CPS driven by new requirements and competitive pressures.

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.