Ontological Framework to Model Critical Infrastructures and their Interdependencies

Castorini, Elisa; Palazzari, P.; Tofani, Alberto; Servillo, Paolo

doi:10.1109/compeng.2010.25

Cited by 6 publications

(3 citation statements)

References 6 publications

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“…Masucci et al [42] discuss the derivation of ontology components and their relationships using OWL and SWRL. Castorini et al [5] describe an application involving the power grid, railway and telecommunication domains, and their mutual relationships. Interested readers are referred to [63,70] for more details.…”

Section: Critical Infrastructure Simulationmentioning

confidence: 99%

Exploiting Web Ontologies for Automated Critical Infrastructure Data Retrieval

Galbusera

Giannopoulos

2017

Critical Infrastructure Protection XI

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Semantic web technologies play a significant role in many open data initiatives, including geo-mapping projects and platforms. At the same time, semantic principles are also promoted as a key enabling factor for multi-domain analyses of critical infrastructures as well as for improved emergency response. This chapter reviews the recent literature on ontology-based analysis and management of critical infrastructures, and proposes the use of ontology processing techniques to bridge the gap between infrastructure knowledge representation and available (often general-purpose) open data sources. In particular, it discusses an approach for matching a given critical infrastructure ontology to an ontology built on OpenStreetMap (OSM) tags that enables structured access to the associated geographical dataset.

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Section: Critical Infrastructure Simulationmentioning

confidence: 99%

Exploiting Web Ontologies for Automated Critical Infrastructure Data Retrieval

Galbusera

Giannopoulos

2017

Critical Infrastructure Protection XI

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“…As a result, the protection of Critical Infrastructures has drown major research interest particularly focusing on modelling, analysis and simulation of the processes [13][14][15][16][17][18]. In addition, the research that mainly targets small-scale systems is inadequate to reflect the complexity of these infrastructures [19] and does not include various types of attacks [20].…”

mentioning

confidence: 99%

A Robust Information Life Cycle Management Framework for Securing and Governing Critical Infrastructure Systems

et al. 2018

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In modern societies, the rampant growth of the Internet, both on the technological and social level, has created fertile ground for the emergence of new types of risk. On top of that, it enhances pre-existing threats by offering new means for accessing and exploiting Critical Infrastructures. As the kinds of potential threats evolve, the security, safety and resilience of these infrastructures must be updated accordingly, both at a prevention, as well as a real-time confrontation level. Our research approaches the security of these infrastructures with a focus on the data and utilization of every possible piece of information that derives from this ecosystem. Such a task is quite daunting, since the quantity of data that requires processing resides in the Big Dataspace. To address this, we introduce a new well-defined Information Life Cycle in order to properly model and optimise the way information flows through a modern security system. This life cycle covers all the possible stages, starting from the collection phase up until the exploitation of information intelligence. That ensures the efficiency of data processing and filtering while increasing both the veracity and validity of the final outcome. In addition, an agile Framework is introduced that is optimised to take full advantage of the Information Life Cycle. As a result, it exploits the generated knowledge taking the correct sequence of actions that will successfully address possible threats. This Framework leverages every possible data source that could provide vital information to Critical Infrastructures by performing analysis and data fusion being able to cope with data variety and variability. At the same time, it orchestrates the pre-existing processes and resources of these infrastructures. Through rigorous testing, it was found that response time against hazards was dramatically decreased. As a result, this Framework is an ideal candidate for strengthening and shielding the infrastructures’ resilience while improving management of the resources used.

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“…There are no standards that exist for cross infrastructure modeling. In a coupled model, however, there are two widely accepted methods for exchanging information between simulations: the High Level Architecture HLA has been more widely used to implement distributed critical infrastructures such as air traffic control and vessel traffic systems [15]; electric grid and its SCADA systems [16]; and telecommunications, railway and electric systems [17]. A similar publish-subscribe communication paradigm is called Quality of Service Descriptors that has been implemented in a grid architecture for the electrical grid to aid in information sharing among critical infrastructures [18].…”

Section: Coupled Modelmentioning

confidence: 99%

CIMoRE: Developing a framework for a critical infrastructure modeling and response environment

Rursch

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Ontological Framework to Model Critical Infrastructures and their Interdependencies

Cited by 6 publications

References 6 publications

Exploiting Web Ontologies for Automated Critical Infrastructure Data Retrieval

Exploiting Web Ontologies for Automated Critical Infrastructure Data Retrieval

A Robust Information Life Cycle Management Framework for Securing and Governing Critical Infrastructure Systems

CIMoRE: Developing a framework for a critical infrastructure modeling and response environment

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