No abstract

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.

Decision Support Systems (DSS) are complex technological tools, which enable an accurate and complete scenario awareness, by integrating data from both "external" (physical) situation and current behaviour and state of functioning of the technological systems. The aim is to produce a scenario analysis and to guess identify educated the most efficient strategies to cope with possible crises. In the domain of Critical Infrastructures (CI) Protection, DSS can be used to support strategy elaboration from CI operators, to improve emergency managers capabilities, to improve quality and efficiency of preparedness actions. For these reasons, the EU project CIPRNet, among others, has realised a new DSS designed to help operators to deal with the complex task of managing multi-sectorial CI crises, due to natural events, where many different CI might be involved, either directly or via cascading effects produced by (inter-)dependency mechanisms. This DSS, called CIPCast, is able to produce a real-time operational risk forecast of CI in a given area; other than usable in a real-time mode, CIPCast could also be used as scenario builder, by using event simulators enabling the simulation of synthetic events whose impacts on CI could be emulated. A major improvement of CIPCast is its capability of measuring societal consequences related to the unavailability of primary services such as those delivered by CI.

Time series can be transformed into graphs called horizontal visibility graphs (HVGs) in order to gain useful insights. Here, the maximum eigenvalue of the adjacency matrix associated to the HVG derived from several time series is calculated. The maximum eigenvalue methodology is able to discriminate between chaos and randomness and is suitable for short time series, hence for experimental results. An application to the United States gross domestic product data is given.

This paper describes a knowledge-based system (KBS) designed to support a federated environment for simulating critical infrastructure models. A federation of simulators is essentially a "system of systems," where each simulator represents an entity that operates independently with its own behavior and purpose. The interactions among the components of the federated system of systems exhibit critical infrastructure vulnerabilities as emergent behavior; these vulnerabilities cannot be analyzed and simulated by considering the behavior of each system component individually. The KBS, which is based on ontologies and rules, provides a semantic foundation for the federated simulation environment and enables the dynamic binding of different critical infrastructure models. The KBS-based simulation environment can be used to identify latent critical infrastructure interdependencies and to test assumptions about interdependencies.