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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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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Daniel Lichte, Dustin Witte, & Kai-Dietrich Wolf. (2020). Comprehensive Security Hazard Analysis for Transmission Systems. 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. 1145–1153). Blacksburg, VA (USA): Virginia Tech.
Abstract: Critical energy infrastructures are more and more focused upon by politics and society. Modern society depends on these structures, since they enable the steady support of electricity and other types of energy. Deliberately precipitated hazards of certain critical parts of electrical transmission systems (ETS) can lead to catastrophic consequences. Therefore, the analysis of feasible security hazards and resulting consequences for the operation of transmission systems are a concern to transmission system operators (TSO). Alas, there is no common method available that comprehensively identifies these feasible security related scenarios and classifies them according to their overall criticality for the safe operation of the ETS. To tackle this challenge, we propose a comprehensive, yet easy-to-apply method to systematically identify and assess the criticality of security threat scenarios. It is conducted in four steps and consists of a matrix based consistency check of threat scenarios in a defined solution space and a convenient semi-quantitative assessment of a risk factor for the ETS. The approach is illustrated by the simplified generic example of an EETS.
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Gabriel, A., & Torres, F. S. (2023). Navigating Towards Safe and Secure Offshore Wind Farms: An Indicator Based Approach in the German North and Baltic Sea. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 609–619). Omaha, USA: University of Nebraska at Omaha.
Abstract: Offshore wind farms (OWFs) have become an increasingly relevant form of renewable energy in recent years, with the German North Sea being one of the most active regions in the world. However, the safety and security of OWF have become increasingly important due to the potential threats and risks associated with their growing share in the security of energy supply. This paper aims to present a comprehensive and systematic indicator-based approach to assess the safety and security status of OWFs in the German North Sea. The approach is based on the results of a survey of people working in the offshore industry and draws on the work published by Gabriel et al. (2022). The results of the study suggest that the indicator-based approach is a useful tool for end users to assess the security status of offshore wind farms and can be used for further research and development.
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Xiaofeng Hu, Shifei Shen, & Jiansong Wu. (2012). Modeling of attacking and defending strategies in situations with intentional threats. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Intentional threats including terrorism have become a worldwide catastrophe risk since recent years. To protect the cities from being attacked, the macro-level study of decision analysis should be given more considerations. In this paper, we proposed a model for describing the strategic game between attackers and defenders based on the methodology of matrix game. This model can be employed to determine which target will be selected by attackers and which attacking strategy and defending strategy will be chosen by attackers and defenders respectively. Furthermore, the defenders of the city can use this model to set priorities among their defending strategies. The importance of this work is to establish a reasonable framework for modeling the attacking and defending strategies rather than assessing the real risk of urban targets, so the model is illustrated by using fictitious numbers. The model proposed in this paper can provide scientific basis for macroscopic decision making in responding to intentional threats. © 2012 ISCRAM.
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George Leventakis, Athanasios Sfetsos, Vasileios Gkrizis, Nikolas Athanasiadis, Stefan Tönjes, Spyros Kopsidas, et al. (2011). A Security Risk Analysis Framework for interconnected transportation systems. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The present paper introduces a comprehensive Transportation Security Risk Assessment Framework for assessing related risks and provides cohered contingency management procedures in interconnected, interdependent and heterogeneous transport networks. The proposed approach includes elements, methodological tools and approaches found in the literature, in addition to operational experience from the organization of major events.
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Lida Huang, Guoray Cai, Hongyong Yuan, Jianguo Chen, Yan Wang, & Feng Sun. (2018). Modeling Threats of Mass Incidents Using Scenario-based Bayesian Network Reasoning. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 121–134). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Mass incidents represent a global problem, putting potential threats to public safety. Due to the complexity and uncertainties of mass incidents, law enforcement agencies lack analytical models and structured processes for anticipating potential threats. To address such challenge, this paper presents a threat analysis framework combining the scenario analysis method and Bayesian network (BN) reasoning. Based on a case library
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Kathryn Toelken, Matthew W. Seeger, & Allen Batteau. (2005). Learning and renewal following threat and crisis: The experience of a computer services firm in response to Y2K and 9/11. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 43–51). Brussels: Royal Flemish Academy of Belgium.
Abstract: This paper reports on a research project in progress. This project is an investigation of the ways in which organizations learn in response to threats and crises. Considerable scholarship in organizational learning theory, renewal, and in organizational crisis suggests that the ability of organizations to learn and reconstitute themselves is a critical capacity for successfully responding to crises and threats. These learning processes are examined within the context of a global, Fortune 100 computer services firm and its response to the Y2K threat and the 9/11 crisis.
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Vitaveska Lanfranchi, Nadia Noori, & Tudor Sirbu. (2018). GPS-based solution for tracking and protecting humanitarians in conflict zones. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 334–349). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: The operational environment in which humanitarians operate is unstable and high-risk; when operating in such environments, time becomes a critical factor. Thus, real-time location systems (RTLS) are often deployed in the operational environment to provide awareness of the location of personnel and assets in real-time that would support an informed decision making in the event of responding to emergency. Whilst standard RTLS are very precise, they are not suitable to outdoor spaces; GPS position technology can be used to identify the location of objects and people and to track them. In this paper, first, we present a description of threat scenarios identified based on information from existing security incidents datasets and from interviews with aid workers and security professionals operating in high-risk regions. Second, we describe the implementation of a GPS-based real-time location tracking and alert system for humanitarians operating in conflict zones that supports the identified scenarios.
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Matt Wolff. (2010). Unsupervised methods for detecting a malicious insider. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: One way a malicious insider can attack a network is by masquerading as a different user. Various algorithms have been proposed in an effort to detect when a user masquerade attack has occurred. In this paper, two unsupervised algorithms are proposed with the intended goal of detecting user masquerade attacks. The effectiveness of these two unsupervised algorithms are then compared against supervised algorithms.
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