Biblio
NIST, in collaboration with Vanderbilt University, has assembled an open-source tool set for designing and implementing federated, collaborative and interactive experiments with cyber-physical systems (CPS). These capabilities are used in our research on CPS at scale for Smart Grid, Smart Transportation, IoT and Smart Cities. This tool set, "Universal CPS Environment for Federation (UCEF)," includes a virtual machine (VM) to house the development environment, a graphical experiment designer, a model repository, and an initial set of integrated tools including the ability to compose Java, C++, MATLABTM, OMNeT++, GridLAB-D, and LabVIEWTM based federates into consolidated experiments. The experiments themselves are orchestrated using a ‘federation manager federate,’ and progressed using courses of action (COA) experiment descriptions. UCEF utilizes a method of uniformly wrapping federates into a federation. The UCEF VM is an integrated toolset for creating and running these experiments and uses High Level Architecture (HLA) Evolved to facilitate the underlying messaging and experiment orchestration. Our paper introduces the requirements and implementation of the UCEF technology and indicates how we intend to use it in CPS Measurement Science.
In the past couple of years, railway infrastructure has been growing more connected, resembling more of a traditional Cyber-Physical System model. Due to the tightly coupled nature between the cyber and physical domains, new attack vectors are emerging that create an avenue for remote hijacking of system components not designed to withstand such attacks. As such, best practice cybersecurity techniques need to be put in place to ensure the safety and resiliency of future railway designs, as well as infrastructure already in the field. However, traditional large-scale experimental evaluation that involves evaluating a large set of variables by running a design of experiments (DOE) may not always be practical and might not provide conclusive results. In addition, to achieve scalable experimentation, the modeling abstractions, simulation configurations, and experiment scenarios must be designed according to the analysis goals of the evaluations. Thus, it is useful to target a set of key operational metrics for evaluation and configure and extend the traditional DOE methods using these metrics. In this work, we present a metrics-driven evaluation approach for evaluating the security and resilience of railway critical infrastructure using a distributed simulation framework. A case study with experiment results is provided that demonstrates the capabilities of our testbed.