University of Oulu

Schaberreiter, T., Wills, C., Quirchmayr, G. & Röning, J. (2017). Addressing complex problem situations in critical infrastructures using soft systems analysis : the CS-AWARE approach. In C. M. Westphall, H. Hof, A. Olmsted, S. Schauer, M. Latzenhofer, A. Abidin & G. Yee (Eds.), SECURWARE 2017 : the Eleventh International Conference on Emerging Security Information, Systems and Technologies (pp. 99-105). IARIA.

Addressing complex problem situations in critical infrastructures using soft systems analysis : the CS-AWARE approach

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Author: Schaberreiter, Thomas1; Wills, Chris2; Quirchmayr, Gerald1;
Organizations: 1Faculty of Computer Science, University of Vienna (Vienna, Austria)
2CARIS Research Ltd. (Fowey, United Kingdom)
3Faculty of Information Technology and Electrical Engineering, University of Oulu (Oulu, Finland)
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.4 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019070522813
Language: English
Published: International Academy, Research, and Industry Association, 2017
Publish Date: 2019-07-05
Description:

Abstract

In a world in which large-scale cyber attacks are the norm rather than the exception, the need for cybersecurity gains in importance every day. Current cybersecurity solutions are often not taking the holistic approach that would be required to provide comprehensive security to their users (for example, strategic/critical infrastructure, large organizations, small and medium-sized enterprises (SMEs) or public institutions). A new way of thinking about cybersecurity is required: Cooperation and collaboration among individual actors as a way to improve the security situation for society and economy as a whole is a promising approach. In the European Union, the legal framework that is currently developing (like the network and information security (NIS) directive), recognizes the need for cooperation and collaboration among individual actors to improve cybersecurity. Information sharing is one of the key elements of the NIS directive. In this paper, we present a system and dependency analysis based on soft systems thinking that is able to capture the relations between assets and its internal and external dependencies in the complex systems of organizations like critical infrastructures or other organizations that base their operations on complex systems and interactions. The analysis is done in a socio-technological manner; the human aspect of the systems is considered as important as the technical or organizational aspects. As a use case, we present CS-AWARE, a European H2020 project which relies on the presented system and dependency analysis method as a core concept for providing a cybersecurity solution that is in line with the cooperative and collaborative efforts of the NIS directive.

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ISBN: 978-1-61208-582-1
Pages: 99 - 105
Host publication: SECURWARE 2017 : the Eleventh International Conference on Emerging Security Information, Systems and Technologies
Host publication editor: Westphall, Carla Merkle
Hof, Hans-Joachim
Olmsted, Aspen
Schauer, Stefan
Latzenhofer, Martin
Abidin, Aysajan
Yee, George
Conference: SECURWARE 2017 : the Eleventh International Conference on Emerging Security Information, Systems and Technologies
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Subjects:
Funding: We would like to thank the EU H2020 project CS-AWARE ("A cybersecurity situational awareness and information sharing solution for local public administrations based on advanced big data analysis", project number 740723) and the Austrian national KIRAS project CERBERUS ("Cross Sectoral Risk Management for Object Protection of Critical Infrastructures", project number 854766) for supporting this work. The Biomimetics and Intelligent Systems Group (BISG) would like to acknowledge the support of Infotech Oulu.
EU Grant Number: (740723) CS-AWARE - A cybersecurity situational awareness and information sharing solution for local public administrations based on advanced big data analysis
Copyright information: © IARIA, 2017. Published in this repository with the kind permission of the publisher.