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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: hdl:10419/228914

Classification and Topics

• Classification: Management
• Subject: Logistics ; Industry 4.0 ; Digitalization ; Innovation ; Supply Chain Management ; Artificial Intelligence ; Data Science

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): König, Sandra
• Event: Veröffentlichung
• (who): epubli GmbH
• (where): Berlin
• (when): 2020

Further information

• DOI: doi:10.15480/882.3123
• Handle: http://hdl.handle.net/10419/228924
• URN: urn:nbn:de:gbv:830-882.0115084
• Last update: 10.03.2025, 11:42 AM CET