Selection of Pareto-efficient response plans based on financial and operational assessments

被引：6
作者：
Motzek A. [2 ]
Gonzalez-Granadillo G. [1 ]
Debar H. [1 ]
Garcia-Alfaro J. [1 ]
Möller R. [2 ]
机构：
[1] SAMOVAR, Telecom SudParis, CNRS, Université Paris-Saclay, 9 Rue Charles Fourier, Evry
[2] Universität zu Lübeck, Institute of Information Systems, Ratzeburger Allee 160, Lübeck
来源：
Eurasip Journal on Information Security | 2017年 / 2017卷 / 01期
关键词：
Dynamic response; Financial impact; Impact assessment; Operational impact; Pareto-efficiency;
D O I：
10.1186/s13635-017-0063-6
中图分类号：
学科分类号：
摘要：
Finding adequate responses to ongoing attacks on ICT systems is a pertinacious problem and requires assessments from different perpendicular viewpoints. However, current research focuses on reducing the impact of an attack irregardless of side effects caused by responses. In order to achieve a comprehensive yet accurate response to possible and ongoing attacks on a managed ICT system, we propose an approach that evaluates a response from two perpendicular perspectives: (1) A response financial impact assessment, considering the financial benefits of restoring and protecting potentially threatened operational capabilities while considering implementation and maintenance costs of responses. (2) A response operational impact assessment, which assesses potential impacts that efficient mitigation actions may inadvertently cause on the organization in an operational perspective, e.g., negative side effects of deploying mitigations. It is the key benefit of the presented approach to combine all obtained evaluations with a multi-dimensional optimization procedure such that a response plan is selected which reduces a state of risk below an admissible level while minimizing potential negative side effects of deliberately taken actions. © 2017, The Author(s).
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  • [1] Dini G., Tiloca M., On simulative analysis of attack impact in Wireless Sensor Networks, ETFA2013: 18th Conference on Emerging Technologies & Factory Automation, pp. 1-8, (2013)
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  • [3] Su P., Chen X., Tang H., DoS attack impact assessment based on 3GPP QoS indexes, 3rd International Conference on Innovative Computing Information and Control, (2008)
  • [4] Sgouras K.I., Birda A.D., Labridis D.P., Cyber attack impact on critical smart grid infrastructures, ISGT2014: Innovative Smart Grid Technologies Conference, pp. 1-5, (2014)
  • [5] Roberts B.W., The macroeconomic impacts of the 9/11 attack: evidence from real-time forecasting. Peace Economics, Peace Science and Public Policy, 15, (2009)
  • [6] Gonzalez-Granadillo G., Motzek A., Garcia-Alfaro J., Debar H., Selection of mitigation actions based on financial and operational impact assessments, ARES2016: 11th International Conference on Availability, Reliability, and Security, pp. 137-146, (2016)
  • [7] Gonzalez-Granadillo G., Belhaouane M., Debar H., Jacob G., RORI-based countermeasure selection using the OrBAC formalism, Int. J. Inf. Secur, 13, 1, pp. 63-79, (2014)
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  • [9] Gonzalez-Granadillo G., Debar D., Jacob G., Gaber C., Achemlal M., Individual countermeasure selection based on the return on response investment index, MMM-ACNS2012: International Conference Mathematical Methods, Models and Architectures for Computer Network Security, pp. 156-170, (2012)
  • [10] Motzek A., Moller R., Lange M., Dubus S., Probabilistic mission impact assessment based on widespread local events, NATO IST-128 Workshop: Assessing Mission Impact of Cyberattacks, pp. 16-22, (2015)
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