Alexander Gabriel, Florian Klein, & Frank Fiedrich. (2020). Modelling of Passenger Handling Processes in Railway Stations – A Mixed-Methods Approach. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 580–592). Blacksburg, VA (USA): Virginia Tech.
Abstract: The constantly increasing number of passengers using public transportation leads to an expansion of the ser-vices offered by public transportation companies. The existing transportation infrastructures, especially rail-way stations, can only partly cope with this rapid growth. There is already overcrowding on platforms and access routes, especially during disruptions caused by natural disasters or major public events. This crowding may result in personal injury or shutdown of operations for safety reasons. The research project CroMa aims at improving robustness, safety, security and performance of railway stations at peak loads. The paper contributes thereto by developing an approach to assess railway infrastructure in terms of the risk of overcrowding. The core of this research is to combine qualitative workshop results with quantitative database analysis. Furthermore, the paper gives an outlook on the ongoing process model development as a basis for a semi-quantitative evaluation tool for railway stations applicable by end users.
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Andreas Lotter, Florian Brauner, Alexander Gabriel, Frank Fiedrich, & Stefan Martini. (2017). New Decision-Support Framework for Strengthening Disaster Resilience in Cross-Border Areas. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 412–419). Albi, France: Iscram.
Abstract: The improvement of disaster resilience in cross-border areas causes special challenges. Involved countries use different structures in their civil protection systems and have to work together facing more difficult conditions than in local incidents. Furthermore, in the past involved countries mainly worked individually and focused on the concerned areas in their territories regardless transnational activities. The project INCA will develop a resilience framework to support decision-makers. The framework will focus on information management, the implementation of volunteers and the needs of citizens who are receiving medical care. Therefore, a case study region on the German-French border was defined and a scenario-based approach will be used to investigate resilience opportunities through disaster collaboration. The tested scenario is a transnational long-lasting power-outage in the German-French region.
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Alexander Gabriel, Simon Schleiner, Florian Brauner, Florian Steyer, Verena Gellenbeck, & Ompe Aimé Mudimu. (2017). Process modelling of physical and cyber terrorist attacks on networks of public transportation infrastructure. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 390–399). Albi, France: Iscram.
Abstract: Recent events have demonstrated the vulnerability of IT-systems of different companies, organisations or even governments to hacker attacks. Simultaneously, information technologies have become increasingly established and important for institutions of various branches. With respect to modern terrorism developments, cyber-attacks may be used to physically harm critical infrastructures. This leads to a new dimension of cyber-attacks called “terrorist cyber-attacks”. This research-in-progress paper aims to develop a process model for data acquisition and support of decision making that seeks to enhance the security of public transportation in the context of counterterrorism. Therefore, a generic process model for terrorist cyber-attacks – produced in the research project RE(H)STRAIN1 – is intro-duced as a basis for a decision support system (DSS). In the future, such models could improve the decision process by comparing the effectiveness of different security measures.
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Alexander Gabriel, Florian Brauner, Andreas Lotter, Frank Fiedrich, & Ompe Aimé Mudimu. (2018). The determination of critical components of European Rail Traffic Management systems towards cyber-attacks. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 291–303). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: “Recent events have shown the vulnerability of IT systems of companies, organizations or even governments to hacker attacks. At the same time, information technologies are becoming increasingly established and important in various industries (digitalization). With a view to the modern development of terrorism, cyber-attacks can be used to physically damage critical infrastructures (CI). This leads to a new dimension of cyber-attacks, which are called terrorist cyber-attacks. The following research contributes to the identification of weak information technology components of railway operating systems and thus improves the safety of public transportation in the context of the European railway traffic management system (ERTMS). The core of this paper is an extended literature research on security flaws in the ERTMS. The future introduction of a methodology for evaluating the criticality of information technology system components will build on this using cyber threats and public transportation as examples.”
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Alexander Gabriel, Babette Tecklenburg, Yann Guillouet, & Frank Sill Torres. (2021). Threat analysis of offshore wind farms by Bayesian networks – a new modeling approach. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 174–185). Blacksburg, VA (USA): Virginia Tech.
Abstract: As a result of the ongoing commitment to climate protection in more and more countries and the corresponding expansion of renewable energies, the importance of renewables for the security of electricity supply is also increasing. Wind energy generated in offshore wind farms already accounts for a significant share of the energy mix and will continue to grow in the future. Therefore, approaches and models for security assessment and protection against threats are also needed for these infrastructures. Due to the special characteristics and geographical location of offshore wind farms, they are confronted with particular challenges. In this context, this contribution outlines how an approach for threat analysis of offshore wind farms is to be developed within the framework of the new research project “ARROWS” of the German Aerospace Center. The authors first explain the structure of offshore wind farms and then present a possible modeling approach using Qualitative function models and Bayesian networks.
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Alexander Gabriel, Babette Tecklenburg, & Frank Sill Torres. (2022). Threat and Risk Scenarios for Offshore Wind Farms and an Approach to their Assessment. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 162–173). Tarbes, France.
Abstract: Offshore wind farms in the German North and Baltic Seas have a key role to play in the context of the shift towards renewable energy and in securing electricity supplies in the future. At the same time, however, shipping routes in the North and Baltic Seas are among the busiest in the world, wind farms are increasingly being operated unmanned and conflicts increasingly involve a hybrid element. From these constellations and competing interests, various risk and threat scenarios emerge. By means of a survey among experts from offshore wind industry, this paper first captures the subjective assessment of the risk situation in order to subsequently develop an approach for their evaluation. The paper uses Bayesian networks in order to enable a risk assessment also under inclusion of uncertain parameters.
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