Improving risk assessment for interdependent urban critical infrastructures

Konferenzbeitrag

Purpose: Urban critical infrastructures are highly interdependent not only due to their vicinity but also due to the increasing digitalization. In case of a security incident, both the dynamics inside each infrastructure and interdependencies between them need to be considered to estimate the overall impact on a city. Methodology: An existing high-level model of dependencies between critical infrastructures is extended by incorporating more details on the individual infrastructure's behavior. To this end, a literature review on existing models for specific sectors is conducted with a special focus on machine learning models such as neural net-works. Findings: Existing models for the dynamics of specific urban infrastructures are reviewed and integration in an existing dependency model is discussed. A special focus lies on simulation models since the extended model should be used to evaluate consequences of a security incident in a city. Originality: Existing risk assessment approaches typically focus on one type of critical infrastructures rather than on an entire network of interdependent infrastructures. However due to the increasing number of interdependencies, a more holistic view is necessary while the dynamics inside each infrastructure should also be considered.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: hdl:10419/228914

Klassifikation und Themen

• Klassifikation: Management
• Thema: Logistics ; Industry 4.0 ; Digitalization ; Innovation ; Supply Chain Management ; Artificial Intelligence ; Data Science

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): König, Sandra
• Ereignis: Veröffentlichung
• (wer): epubli GmbH
• (wo): Berlin
• (wann): 2020

Weitere Informationen

• DOI: doi:10.15480/882.3123
• Handle: http://hdl.handle.net/10419/228924
• URN: urn:nbn:de:gbv:830-882.0115084
• Letzte Aktualisierung: 10.03.2025, 11:42 MEZ