Classification, Prioritization, Intrinsic Value, Critical Infrastructure, Assets, Indices, Best-Worst.
Subject Areas :Gholam reza hossein ali beyki 1 , Abbas Akbarpoor Nikghalb Rashti 2 , Seyed Azim Hosseini 3 , Hamidreza Abbasian Jahromi 4
1 - PhD Student, Department of Civil Engineering, Faculty of Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
2 - Assistant Professor, Department of Civil Engineering, Faculty of Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
3 - Assistant Professor, Department of Civil Engineering, Faculty of Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
4 - Assistant Professor, Department of Engineering and Construction Management, Faculty of Civil Engineering, K.N. Toosi University of Technology, Tehran, Iran
Keywords: Classification, prioritization, Indices, intrinsic value, Critical Infrastructure, Best-Worst,
Abstract :
Today, the growth and development of societies in economic, social, political, public health and security dimensions depends on the performance of critical infrastructure. Infrastructure management and management is one of the most important concerns in this field to ensure their proper performance and sustainability against the risks ahead. Securing and safeguarding critical infrastructure and key assets against all risks, factors and adverse conditions is one of the most challenging issues for governments due to limited financial resources. One way to overcome these limitations is to prioritize and classify infrastructure. Proper determination of priorities, using measurable indicators, in addition to distinguishing critical assets and infrastructure from non-critical ones, leads to optimal resource management and increases the effectiveness of measures to protect critical infrastructure. The main purpose of this study is to evaluate and validate the indicators of the vitality of critical infrastructure and determine the weight of each indicator by the best-worst method. The results of studies performed on 26 initial indicators and the validity and reliability of the indicators led to the final confirmation of 24 indicators. Weighting of indicators was done according to the best-worst method (BWM). Based on calculations based on the opinions of selected experts, the index "Number of population at risk" with a weight of 8.5%, "Independence and territorial integrity" with a weight of 7.8% and "Defense capability" with a weight of 7.8%, respectively, have the highest weight and importance. Are assigned among the indicators.
Aaron Burkhart, (2017), Lifeline Infrastructure Risk Analysis Application, University of Colorado at Colorado Springs, 2015.
"CTED" Trends Report, (2017), Physical Protection Of Critical Infrastructure A gainst Terrorist Attacks.
Dvorak, Z., Sventekova, E.,(2013), Evaluation of the resistance critical infrastructure in Slovak Republic, (JEMC) Vol. 3, No. 1, 2013, 1-5.
Dvorak, Z., Sventekov E., Rehak, D., Cekerevac, Z., (2017), Assessment of Critical Infrastructure Elements in Transport, Procedia Engineering 187, 548 – 555, https://doi.org /10.1016 / j.proeng.2017.04.413.
European Council, Council Directive 2008/114/EC of 8 December 2008, on the Identification and Designation of European Critical Infrastructures and the Assessment of the Need to Improve Their Protection, Brussels, Belgium.
Feofilovs, M., Romagnoli, F., (2017), Resilience of critical infrastructures: probabilistic case study of a district heating pipeline network in municipality of Latvia, Energy Procedia 128, 17–23, http://dx.doi.org/10.1016/j.egypro.2017.09.007.
Hempel, L., Kraff D., Pelzer R., (2018), Dynamic Interdependencies: Problematising Criticality Assessment in the Light of Cascading Effects, International Journal of Disaster Risk Reduction, https://doi.org/10.1016/j.ijdrr.2018.04.011.
Labaka, L., Hernantes, J., Sarriegi, J.M., (2016), A holistic framework for building critical infrastructure resilience, Technological Forecasting & Social Change 103, 21–33, http://dx. doi.org/10.1016/j.techfore.2015.11.005.
Lewis, T.G., Darken, R.P., Mackin, T., Dudenhoeffer, D., (2012), Model-based risk analysis for critical infrastructures, " ISSN 1755-8336 (2012)" https://doi.org/ 10.2495/978-1-84564-562-5/01.
Mikellidou, C.V., Shakou, L.M., Boustras, G., Dimopoulos C., (2017), Energy critical infrastructures at risk from climate change: A state of the art Review, Safety Science, https://doi.org/10.1016/j.ssci.2017.12.022.
Muller, G., (2012), Fuzzy architecture assessment for critical infrastructure resilience, Procedia Computer Science 12, 367–372, https://doi.org/10.1016/j.procs.2012.09.086.
National Strategy for the Physical Protection of Critical Infrastructures and Key Assets (PPCIKA), (2003).
Pederson, P., Dudenhoeffer D.,, Hartley, S., Permann, M., (2006), Critical Infrastructure Interdependency Modeling: A Survey of U.S. and International Research, Idaho National Laboratory Idaho Falls, Idaho 83415, INL/EXT-06-11464.
Rehak, D., Markuci, J., Hromada, M., Barcova, K., (2016), Quantitative evaluation of the synergistic effects of failures in a critical infrastructure system, international journalof critical infrastructure protection1 4, 3–17, http://dx.doi.org/10.1016/j.ijcip.2016.06.002.
Rezaei, j. (2015), Best-worst muliti-criteria decision-making method. Omega, 53, 49-57.
Serre, D., Heinzlef, C., (2018), Assessing and mapping urban resilience to floods with respect to cascading effects through critical infrastructure networks, International Journal of Disaster Risk Reduction, https://doi.org/10.1016/j.ijdrr.2018.02.018.
Sullivant, j., (2007), Strategise for Protecting National Critical Infrastructure Assets, ISBN: 978-0-471-79926-9.
Taylor, (2017), Vulnerability Analysis for Transportation Networks, ISBN: 978-0-12-811010-2, http://dx.doi.org/10.1016/B978-0-12-811010-2.00002-2.
UNISDR, (2017), National Disaster Risk Assessment, United Nations Office for Disaster Risk Reduction (UNISDR).
_||_Aaron Burkhart, (2017), Lifeline Infrastructure Risk Analysis Application, University of Colorado at Colorado Springs, 2015.
"CTED" Trends Report, (2017), Physical Protection Of Critical Infrastructure A gainst Terrorist Attacks.
Dvorak, Z., Sventekova, E.,(2013), Evaluation of the resistance critical infrastructure in Slovak Republic, (JEMC) Vol. 3, No. 1, 2013, 1-5.
Dvorak, Z., Sventekov E., Rehak, D., Cekerevac, Z., (2017), Assessment of Critical Infrastructure Elements in Transport, Procedia Engineering 187, 548 – 555, https://doi.org /10.1016 / j.proeng.2017.04.413.
European Council, Council Directive 2008/114/EC of 8 December 2008, on the Identification and Designation of European Critical Infrastructures and the Assessment of the Need to Improve Their Protection, Brussels, Belgium.
Feofilovs, M., Romagnoli, F., (2017), Resilience of critical infrastructures: probabilistic case study of a district heating pipeline network in municipality of Latvia, Energy Procedia 128, 17–23, http://dx.doi.org/10.1016/j.egypro.2017.09.007.
Hempel, L., Kraff D., Pelzer R., (2018), Dynamic Interdependencies: Problematising Criticality Assessment in the Light of Cascading Effects, International Journal of Disaster Risk Reduction, https://doi.org/10.1016/j.ijdrr.2018.04.011.
Labaka, L., Hernantes, J., Sarriegi, J.M., (2016), A holistic framework for building critical infrastructure resilience, Technological Forecasting & Social Change 103, 21–33, http://dx. doi.org/10.1016/j.techfore.2015.11.005.
Lewis, T.G., Darken, R.P., Mackin, T., Dudenhoeffer, D., (2012), Model-based risk analysis for critical infrastructures, " ISSN 1755-8336 (2012)" https://doi.org/ 10.2495/978-1-84564-562-5/01.
Mikellidou, C.V., Shakou, L.M., Boustras, G., Dimopoulos C., (2017), Energy critical infrastructures at risk from climate change: A state of the art Review, Safety Science, https://doi.org/10.1016/j.ssci.2017.12.022.
Muller, G., (2012), Fuzzy architecture assessment for critical infrastructure resilience, Procedia Computer Science 12, 367–372, https://doi.org/10.1016/j.procs.2012.09.086.
National Strategy for the Physical Protection of Critical Infrastructures and Key Assets (PPCIKA), (2003).
Pederson, P., Dudenhoeffer D.,, Hartley, S., Permann, M., (2006), Critical Infrastructure Interdependency Modeling: A Survey of U.S. and International Research, Idaho National Laboratory Idaho Falls, Idaho 83415, INL/EXT-06-11464.
Rehak, D., Markuci, J., Hromada, M., Barcova, K., (2016), Quantitative evaluation of the synergistic effects of failures in a critical infrastructure system, international journalof critical infrastructure protection1 4, 3–17, http://dx.doi.org/10.1016/j.ijcip.2016.06.002.
Rezaei, j. (2015), Best-worst muliti-criteria decision-making method. Omega, 53, 49-57.
Serre, D., Heinzlef, C., (2018), Assessing and mapping urban resilience to floods with respect to cascading effects through critical infrastructure networks, International Journal of Disaster Risk Reduction, https://doi.org/10.1016/j.ijdrr.2018.02.018.
Sullivant, j., (2007), Strategise for Protecting National Critical Infrastructure Assets, ISBN: 978-0-471-79926-9.
Taylor, (2017), Vulnerability Analysis for Transportation Networks, ISBN: 978-0-12-811010-2, http://dx.doi.org/10.1016/B978-0-12-811010-2.00002-2.
UNISDR, (2017), National Disaster Risk Assessment, United Nations Office for Disaster Risk Reduction (UNISDR).