Information Modelling and Simulation in Large Interdependent Critical Infrastructures in IRRIIS

Klein, Rüdiger; Rome, Erich; Beyel, Cesaire; Linnemann, Ralf; Reinhardt, W.; Usov, Andrij

doi:10.1007/978-3-642-03552-4_4

Cited by 20 publications

(8 citation statements)

References 5 publications

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“…Although some remarkable results have been achieved for selected regions when all the information is available [2], these simulations are not useful in understanding the mechanisms that induce cascading effects. Because of the huge amount of data involved, such an approach requires heroic efforts, even when considering a simple system [3]. Frequently privacy constraints or difficulties in accessing or probing the system of interest become factors, and often an adequate amount of information is not available.…”

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confidence: 99%

Assortativity decreases the robustness of interdependent networks

et al. 2012

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It was recently recognized that interdependencies among different networks can play a crucial role in triggering cascading failures and hence system-wide disasters. A recent model shows how pairs of interdependent networks can exhibit an abrupt percolation transition as failures accumulate. We report on the effects of topology on failure propagation for a model system consisting of two interdependent networks. We find that the internal node correlations in each of the two interdependent networks significantly changes the critical density of failures that triggers the total disruption of the two-network system. Specifically, we find that the assortativity (i.e. the likelihood of nodes with similar degree to be connected) within a single network decreases the robustness of the entire system. The results of this study on the influence of assortativity may provide insights into ways of improving the robustness of network architecture, and thus enhances the level of protection of critical infrastructures.

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confidence: 99%

Assortativity decreases the robustness of interdependent networks

et al. 2012

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“…The EU project IRRIIS [7] aimed at enhancing substantially the dependability of Large Complex Critical Infrastructures. In a holistic approach, IRRIIS developed frameworks, tools and techniques for identifying and understanding the interdependent nature of cumulative risk within such CIs.…”

Section: A Research Projects On Cipmentioning

confidence: 99%

The DIESIS Approach to Semantically Interoperable Federated Critical Infrastructure Simulation

Usov

Beyel

Rome

et al. 2010

2010 Second International Conference on Advances in System Simulation

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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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“…Key challenges include (i) advancing multi-sector critical infrastructure modelling, simulation and analysis (ii) advancing the integration of external factors (human-made and natural threats) and malicious attack (to avoid a widened gap between our ability to design and operate those systems and our capabilities to understand their complex behavior, starting from a recent state of the art assessment [58,59,60,61,62,63,64,65,66,67,68,69,70,71]. Particular breakthroughs include:…”

Section: Critical Infrastructure Securitymentioning

confidence: 99%