Critical infrastructures (CI) such as telecommunication or the power grids and their dependencies are getting increasingly complex. Understanding these -often indirectdependencies is a vital precondition for the prevention of crosssector cascading failures of CI. Simulation is an important tool for CI dependency analysis, the test of methods for risk reduction, and as well for the evaluation of past failures. Moreover, interaction of such simulations with external threat models, e.g., a river flood model and economic models, may assist in what-if decision-making processes. The simulation of complex scenarios involving several different CI sectors requires the usage of heterogeneous federated simulations of CI. However, common standards for modelling and interoperability of such federated CI simulations are missing. In this paper, we present a novel approach for coupling CI simulations, developed and realised in the EU project DIESIS. The DIESIS core technologies for coupling CI simulations include a middleware that enables semantic interoperability of the federate simulators, a systematic, service-oriented approach to set up and run such federations, and, most importantly, a scenario-based architecture concept for modelling and federated simulation of CI. The architecture foresees a flexible pair-wise (lateral) coupling of simulators. DIESIS has implemented a demonstrator as a proof of concept for its approach and technologies, by coupling four different simulation systems (three interacting CIs and an external, common threat). In this paper, we focus on the architectural concept and the interoperability middleware that realises this concept and allows the coupling of heterogeneous simulation systems using various time and data models. We show how the ontology-based Knowledge Based System (KBS) is integrated and used in the overall system. Then, we discuss the basic technical concepts as well as the results obtained with the demonstrator. The proposed architecture is open for further extensions. Ultimately, the proposed approach shall form the basis of a future standard coupling middleware for federated CI simulations.

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Critical Infrastructures (CIs) and their protection play a very important role in modern societies. Today's CIs are managed by sophisticated information systems. These information systems have special views on their respective CIs -but can frequently not manage dependencies with other systems adequately. For dependency analysis and management we need information taking the dependency aspects explicitly into account -in well defined relations to all other relevant kinds of information. This is the aim of the IRRIIS Information Model. It is a semantic model or ontology of CI dependencies. This Information Model allows us to integrate information from different CIs -from real ones as in SCADA systems, or from simulations -in order to manage their interdependencies. This paper gives an overview of the IRRIIS Information Model and the way it is used in the IRRIIS simulator SimCIP for the analysis of interdependent infrastructures. An example will be given to illustrate our approach.

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Cyber-Physical Systems (CPS) are controlled complex technical systems. On one hand they do exist and behave in the physical world with their dedicated physical and technical rules. On the other hand they are controlled according to certain policies - frequently by a "tandem" of control systems and human operators. Modern cars, aircrafts, power grids, production lines etc. are typical cyber-physical systems. The unprecedented technology development has enabled these systems to play an increasingly central role in modern societies. However, to ensure the reliability and effectiveness of CPS operations is always a challenging task since they are often heterogeneous, large-scale and very complex for conventional software systems. In this paper we propose a novel rule-based approach combining deductive and reactive rules to specify and describe CPS. Complex Event Processing (CEP) and Event-Condition-Action (ECA) rules are used to detect situations of interest in CPS and issu ing (complex) control actions, respectively. This allows us to focus on the "what" of CPS control (situation detection, reaction specification) and leaves the "how" to a well defined event and action engine. Whereas events are treated in CPS much the same as in other fields actions are quite different because they happen in the real world. We describe an approach to CPS actions which takes these important particularities into account. Another important issue is the integration of physical models into event and action processing. Temporal aspects play a central role here. Our approach enables us to control CPSs under both normal and exceptional conditions in a flexible and efficient way. In order to illustrate the basic features and expressivities of the proposed approach we consider realistic industrial situations