Quantitative risk-based analysis for military counterterrorism systems

被引:14
|
作者
Kujawski, Edouard [1 ]
Miller, Gregory A. [1 ]
机构
[1] USN, Postgrad Sch, Dept Syst Engn, Monterey, CA 93943 USA
关键词
terrorism; counterterrorism; threats; needs analysis; quantitative probabilistic risk assessment; risk assessment matrix; decision-attack event tree; Monte Carlo simulation; UNCERTAINTIES; TREES;
D O I
10.1002/sys.20075
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper presents a realistic and practical approach to quantitatively assess the risk-reduction capabilities of military counterterrorism systems in terms of damage cost and casualty figures. The comparison of alternatives is thereby based on absolute quantities rather than an aggregated utility or value provided by multicriteria decision analysis methods. The key elements of the approach are (1) the use of decision-attack event trees for modeling and analyzing scenarios, (2) a portfolio model approach for analyzing multiple threats, and (3) the quantitative probabilistic risk assessment matrix for communicating the results. Decision-attack event trees are especially appropriate for modeling and analyzing terrorist attacks where the sequence of events and outcomes are time-sensitive. The actions of the attackers and the defenders are modeled as decisions and the outcomes are modeled as probabilistic events. The quantitative probabilistic risk assessment matrix provides information about the range of the possible outcomes while retaining the simplicity of the classic safety risk assessment matrix based on Mil-Std-882D. it therefore provides a simple and reliable tool for comparing alternatives on the basis of risk including confidence levels rather than single point estimates. This additional valuable information requires minimal additional effort. The proposed approach is illustrated using a simplified but realistic model of a destroyer operating in inland restricted waters. The complex problem of choosing a robust counter-terrorism protection system against multiple terrorist threats is analyzed by introducing a surrogate multi-threat portfolio. The associated risk profile provides a practical approach for assessing the robustness of different counterterrorism systems against plausible terrorist threats. The paper documents the analysis for a hypothetical case of three potential threats. (C) 2007 Wiley Periodicals, Inc.
引用
收藏
页码:273 / 289
页数:17
相关论文
共 50 条
  • [1] Risk-based analysis of manufacturing systems
    Lazov, Igor
    INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2019, 57 (22) : 7089 - 7103
  • [2] Using quantitative analysis to make risk-based decisions
    Farquharson, JA
    McDuffee, JL
    ANNUAL RELIABILITY AND MAINTAINABILITY SYMPOSIUM, 2003 PROCEEDINGS, 2003, : 170 - 176
  • [3] Quantitative risk-based requirements reasoning
    Martin S. Feather
    Steven L. Cornford
    Requirements Engineering, 2003, 8 (4) : 248 - 265
  • [4] Risk-Based Hosting Capacity Analysis in Distribution Systems
    Madavan, Avinash N.
    Dahlin, Nathan
    Bose, Subhonmesh
    Tong, Lang
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2024, 39 (01) : 355 - 365
  • [5] Grading systems for retail food facilities: A risk-based analysis
    Seiver, OH
    Hatfield, TH
    JOURNAL OF ENVIRONMENTAL HEALTH, 2000, 63 (03) : 22 - 27
  • [6] Risk-based analysis tools
    Latcovich, J
    Michalopoulos, E
    Selig, B
    MECHANICAL ENGINEERING, 1998, 120 (11) : 72 - 75
  • [7] RISK-BASED CRITICALITY ANALYSIS
    Theoharidou, Marianthi
    Kotzanikolaou, Panayiotis
    Gritzalis, Dimitris
    CRITICAL INFRASTRUCTURE PROTECTION III, 2009, 311 : 35 - 49
  • [8] On risk-based indices for transmission systems
    Makarov, YV
    Hardiman, RC
    2003 IEEE POWER ENGINEERING SOCIETY GENERAL MEETING, VOLS 1-4, CONFERENCE PROCEEDINGS, 2003, : 671 - 678
  • [9] Synthesis of quantitative and qualitative evidence for accident analysis in risk-based highway planning
    Lambert, James H.
    Peterson, Kenneth D.
    Joshi, Nilesh N.
    ACCIDENT ANALYSIS AND PREVENTION, 2006, 38 (05): : 925 - 935
  • [10] Quantitative comparison of cascading failure models for risk-based decision making in power systems
    David, Alexander E.
    Gjorgiev, Blazhe
    Sansavini, Giovanni
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2020, 198