關鍵基礎設施相依性決策方法與分析

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姓名

曾思敏(Ssu-Min Tseng) 查詢紙本館藏

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土木工程學系

論文名稱

關鍵基礎設施相依性決策方法與分析
(Critical Infrastructure Interdependency: Analysis and Strategic Decision Making)

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摘要(中)

關鍵基礎設施(Critical Infrastructure, CI)為國家重要的資產，用以連續地產生或輸送重要貨物或服務，例如公路與鐵路、高速鐵路與捷運設施、機場與港口、通訊設施、輸電與配電設施、發電廠、儲油槽與輸油管線、供水淨水設施、衛生下水道、醫療設施、銀行與財政服務設施等。一般來說，一關鍵基礎設施在正常運轉的過程中，需要依靠其他關鍵基礎設施提供功能或服務，方能持續運轉下去，此一關係稱作關鍵基礎設施相依性(Critical Infrastructure Interdependency, CII)，已被證明為許多設施損毀的問題來源，當災害發生時常產生連鎖反應，使得防救災決策官員措手不及，無法有效保護所謂的關鍵基礎設施，國家安全將遭受更大的危機。
自美國911事件之後，關鍵基礎設施學界開始關心與研究此議題，如Dr. Haimes等人，提出以1973年諾貝爾經濟獎得主Dr. Wassily Leontief之投入產出模型為基礎的模型，稱作設施輸出入停轉模型(Input-output Inoperability Model, IIM)，用以表達與模擬CII。其他學者如Rinaldi等人，則嘗試將關鍵基礎設施視作複雜的、會適應的系統。本研究則從發展防救災所需的決策流程出發，改良IIM法與時間序列關聯資料探勘法(Generalized Sequential Patterns, GSP)，嘗試以IIM尋找某區域內關鍵基礎設施之受攻擊影響最大設施、從整體系統來看之最值得保護設施，與受損時影響最大的設施，並進而對此類設施以GSP法分析在災害演進過程當中，可設置阻斷連鎖反應之防火牆為何等。本研究最後以竹科某晶圓廠區，與台電北區電力系統網路為例，收集與分析關鍵基礎設施相依性，對關鍵基礎設施在災害發生之前與過程中，提供有效的防護策略與應變措施。

摘要(英)

The research discusses applying the inoperability input-output model (IIM) to analysis of critical infrastructure interdependency. The IIM is based on Leontief’s input-output model, which characterizes interdependencies among sectors in the economy. IIM can analyze initial disruptions to a set of sectors and the resulting ripple effects for modeling impacts of premeditated attacks on infrastructure interdependency. The IIM can systemically prioritize and manage the sectors deemed critical and also identify those sectors of which continued operability is critical during recovery. In addition, this research customizes the Generalized Sequential Patterns (GSP) discovery algorithm to analyze infrastructure failure records so that how a Critical Infrastructure Interdependency (CII) relationship evolves can be recognized and blocked. To prove this model, discussion of modeling the facilities in a wafer fabrication facility in the Hsinchu Science and Industrial Park, as well as the power generation and transmission facilities in Northern Taiwan areas and a disaster mitigation approach to stopping CII-related failure events is listed, followed by the analysis results and experts’ evaluations. Disaster mitigation officials can employ the proposed approach to explore CII and to design countermeasures when a disaster hits certain areas.

關鍵字(中)

★ 關鍵基礎設施相依性
★ 投入產出模型
★ 決策輔助
★ 資料探勘
★ 災害防救

關鍵字(英)

★ Critical infrastructure interdependency
★ Decision making
★ Disaster mitigation
★ Data mining
★ Input-output model

論文目次

中文摘要 I
英文摘要 II
誌謝 III
目錄 IV
圖目錄 VII
表目錄 X
緒論 1
1.1 研究背景與動機 1
1.2 研究問題與目的 4
1.3 研究範圍與限制 4
1.4 論文結構 5
第二章研究方法 6
2.1 投入產出分析 6
2.1.1 基本假設 7
2.1.2 基本原理 8
2.1.3 投入產出模型範例 8
2.2 資料探勘 10
2.2.1 資料探勘-關聯性 11
2.2.2 時間序列關聯資料探勘法 11
2.3 決策流程與方法 13
2.3.1 理性決策模型 13
2.4 總結 14
第三章文獻回顧 15
3.1 關鍵基礎設施 15
3.2 關鍵基礎設施相依性 15
3.3 關鍵基礎設施相依性模型設計與應用 19
3.3.1 時間序列關聯資料探勘法 20
3.3.2 關鍵基礎設施相依性知識發現流程 23
3.3.3 阻斷相依關係序列減輕災害損傷 25
3.4 關鍵基礎設施投入產出停轉模型發展簡介 26
3.4.1 IIM相關研究統計 27
3.4.2 IIM重要研究學者與團隊 34
3.4.3 重要文獻分類 36
3.5 文獻評析 38
第四章災害管理決策分析方法發展 40
4.1 確認研究區域內之關鍵基礎設施與成立專家委員會 44
4.2 諮詢專家，依設施重要性分層進行 44
4.3 以IIM法請專家評定設施兩兩相依程度 46
4.4 執行CII分析並請專家評論結果與適當修正 47
4.5 後續分析工作 51
4.6 關鍵基礎設施在災害進程中的相依性分析 52
4.6.1 設施資料蒐集 52
4.6.2 資料格式整合 56
4.6.3 搜尋常見關鍵基礎設施與重視的關鍵基礎設施損害相關序列 59
4.6.4 範例 60
第五章案例驗證與評估 70
5.1 驗證地區-某竹科晶圓廠 70
5.1.1 晶圓廠廠務系統設施 71
5.1.2 關鍵基礎設施相依性分析與專家驗證 76
5.2 驗證地區-台灣北區供電系統 78
5.2.1 台灣北區供電系統設施 79
5.2.2 關鍵基礎設施相依性分析與專家驗證 83
第六章結論 86
6.1 結論 86
6.2 建議 88
6.3 貢獻 89
參考文獻 90

參考文獻

王塗發. (1986) “投入產出分析及其應用-台灣地區實證研究.”台灣銀行季刊, 37(1), pp. 186-218.
中華電信. (2009) 服務公告資料. 取自：http://www.cht.com.tw/ (2009/12/31)
台灣電力公司. (2011) 網頁公告資料. 取自：http://www.taipower.com.tw/ (2011/12/31)
主計處. (2007) 產業關聯表編製報告, 行政院主計處.
行政院經濟建設委員會. (1978) 投入產出表及分析, 行政院經濟建設委員會綜合計劃處.
陳亮全, 洪鴻智, 詹士樑, and 簡長毅. (2003) “地震災害風險 - 效益分析於土地使用規劃之應用: 應用HAZ-Taiwan 系統.”都市與計劃, 中華民國都市計劃學會, 30(4), pp. 281-299.
謝春棋. (2012) “關鍵基礎設施相依性分析:以竹科某晶圓廠區為例.”碩士論文, 國立中央大學土木工程學系, 桃園, 台灣.
羅俊雄, 葉錦勳, 陳亮全, 洪鴻智, 簡文郁, and 廖文義. (2002) “HAZ-Taiwan地震災害損失評估系統.”台大工程學刊, 國立台灣大學工學院, 85, pp. 13-32.
Barker, K. A. and Haimes, Y. Y. (2009a) “Assessing uncertainty in extreme events: Applications to risk-based decision making in interdependent infrastructure sectors." Reliability Engineering and System Safety, 94(4), pp. 819–82.
Barker, K. A. and Haimes, Y. Y. (2009b) “Uncertainty analysis of interdependencies in dynamic infrastructure recovery: Applications in risk-based decision making." Journal of Infrastructure Systems, 15(4), pp. 394–405.
Barker, K. A. and Santos, J.R. (2010) “A risk-based approach for identifying key economic and infrastructure systems." Risk Analysis, 30(6), pp. 962–974.
Bose, I. and Mahapatra, R. K. (2001). Business data mining—a machine learning perspective. Information & management, 39(3), 211-225.
Chen, L.C., Wu, J.Y., and Lai, M.J. (2006) “The Evolution of the Natural Disaster Management System in Taiwan.” Journal of the Chinese Institute of Engineers, 29(4), pp. 633-638.
Chou, C. C., & Tseng, S. M. (2010). Collection and analysis of critical infrastructure interdependency relationships. Journal of computing in civil engineering, 24(6), 539-547.
Crowther, K. G. and Haimes, Y. Y. (2010) “Development and deployment of the multiregional inoperability input-output model for strategic preparedness." Systems Engineering, 13 (1), pp. 28–46.
Crowther, K. G., Haimes, Y. Y.,and Taub, G. (2007) “Systemic valuation of strategic preparedness through application of the inoperability input-output model with lessons learned from Hurricane Katrina." Risk Analysis, 27(5), pp. 1345-64.
Cuny, F. C. (1983) Disasters and development, Oxford University Press. p. 277.
Fisher, R. and Peerenboom, J. (2000) Interdependencies: A DOE Perspective. 16th Annual Security Technology Symposium & Exhibition, Office of Critical Infrastructure Protection.
Frankfort-Nachmias, C. and Nachmias, D. (1992) Research Methods in the Social Sciences. Edward Arnold, p. 22.
Haimes Y. Y. (1991) “Total Risk Management”. Risk Analysis, Vol. 11, No. 2.
Haimes, Y. Y. (2002) “Roadmap for modeling risks of terrorism to the homeland”. Journal of Infrastructure Systems, 8(2), pp. 35–41.
Haimes, Y. Y. and Horowitz, B. M. (2004) “Modeling Interdependent Infrastructures for Sustainable Counterterrorism.” Journal of Infrastructure Systems, 10(2), pp. 33–41.
Haimes, Y. Y. (2004) Risk modeling, assessment, and management, 2nd Ed., Wiley, New York.
Haimes, Y. Y., Horowitz, B. M., Lambert, J. H., Santos, J. R., Lian, C., and Crowther, K. G. (2005a) “Inoperability input-output model for interdependent infrastructure sectors. I: Theory and methodology.” Journal of Infrastructure Systems, 11(2), pp. 67-79.
Haimes, Y. Y., Horowitz, B. R., Lambert, J. H., Santos, J. R., Crowther, K. G., and Lian, C. (2005b) “Inoperability input-output model (IIM) for interdependent infrastructure sectors. II: Case study.” Journal of Infrastructure Systems, 11(2), pp. 80–92.
Haimes, Y. Y. and Jiang, P. (2001) “Leontief-based model of risk in complex interconnected infrastructures.” Journal of Infrastructure Systems, 7(1), pp. 1–12.
Haimes, Y. Y. (2005) “Infrastructure Interdependencies and Homeland Security.” Journal of Infrastructure Systems, 11(2), pp. 65-66.
Haimes, Y. Y. (2011) "On the Complex Quantification of Risk: Systems-Based Perspective on Terrorism." Risk Analysis, Volume 31, pp. 1175–1186.
Hallegatte, S. (2008) “An adaptive regional input-output model and its application to the assessment of the economic cost of Katrina.” Risk Analysis, 28(3), pp. 779-99.
Hollman, J., Marti, J.R., Jatskevich, J., Srivastava, K.D., (2007) "Dynamic islanding of critical infrastructures: a suitable strategy to survive and mitigate extreme events." International Journal of Emergency Management (IJEM), Volume 4, Issue 1, pp. 2-7.
Huber, W. A. (2010) “Ignorance is not probability.” Risk Analysis, pp. 30(3):371–376.
Jiang, P., and Haimes, Y. Y. (2004) “Risk management for Leontief-based interdependent systems.” Risk Analysis, 24(5), pp. 1215-1229.
Laefer, D., Koss, A., and Pradhan, A. (2006) “The Need for Baseline Data Characteristics for GIS-Based Disaster Management Systems.” Journal of Urban Planning and Development, 132(3), pp. 115-119.
Leontief, W. W. (1951) “Input-output economics.” pp. 15–21.
Leung, M., Haimes, Y. Y., and Santos, J. R. (2007) “Supply- and output-side extensions to the inoperability input -output model for interdependent." Journal of Infrastructure Systems, 13(4), pp. 299–310.
Lian, C., Santos, J. R., and Haimes, Y. Y. (2007) “Extreme risk analysis of interdependent economic and infrastructure sectors.” Risk Analysis, 27(4), pp. 1053–1064.
Lian, C.Y., Santos, J. R., and Haimes, Y. Y. (2006) “Managing the risk of terrorism to interdependent infrastructure systems.” Systems Engineering, 9(3), pp. 241–258.
Mendonca, D. and Wallace, W.A. (2006) “Impacts of the 2001 world trade center attack on New York City critical infrastructures.” Journal of Infrastructure Systems, 12(4), pp. 260-270.
Merriam-Webster. (2003) Merriam-Webster’s Eleventh Collegiate Dictionary, Springfield, Mass., USA.
MRA. (2005) Joint Infrastructure Interdependencies Research Program (JIIRP) Symposium, the Department of Public Safety and Emergency Preparedness Canada (PSEPC), November 10, 2005, Ottawa, Ontario, Canada.
Oosterhaven, J. and Stelder, D. (2002) “Net multipliers avoid exaggerating impacts: With a bi-regional illustration for the Dutch transportation sector.” Journal of Regional Science, 42, pp. 533–543.
Orsi, M. J. and Santos, J. R. (2010a) “Incorporating time-varying perturbations into the dynamic inoperability input–output model.” IEEE Transactions on Systems Man and Cybernetics Part A- Systems and Humans, 40(1), pp. 100–106.
Orsi, M. J. and Santos, J. R. (2010b) “Probabilistic modeling of work force-based disruptions and input–output analysis of interdependent ripple effects.” Economic Systems Research, 22(1), pp. 3–18.
Rahman, H. A., Beznosov, K., & Marti, J. R. (2009). Identification of sources of failures and their propagation in critical infrastructures from 12 years of public failure reports. International Journal of Critical Infrastructures, 5(3), 220-244.
Pederson, P., Dudenhoeffer, D., Hartley, S., and Permann, M. (2006) “Critical Infrastructure Interdependency Modeling: A Survey of U.S. and International Research.” INL/EXT-06-11464, Idaho National Laboratory: Critical Infrastructure Protection Division, Idaho Falls, Idaho.
Percoco, M. (2006) “A note on the inoperability input-output model.” Risk Analysis, 26(30), pp. 589–594.
Percoco, M. (2011) “On the local sensitivity analysis of the inoperability input-output model.” Risk Analysis, 31(7), pp. 1038–1042.
Pradhan, A., Laefer, D., and Rasdorf, W. (2007) "Infrastructure Management Information System Framework Requirements for Disasters." Journal of Computing in Civil Engineering, 21(2), pp. 90-101.
Rinaldi, S., Peerenboom, J., and Kelly, T. (2001) “Identifying, understanding, and analyzing critical infrastructure interdependencies.” IEEE Control Systems Magazine, 21, pp. 11–25.
Santos, J. R. (2008) “Inoperability input-output model (IIM) with multiple probabilistic sector inputs.” Journal of Industrial Management and Optimization, 4(3), pp. 489–510.
Santos, J. R. and Haimes, Y. Y. (2004) “Modeling the demand reduction input-output (I-O) inoperability due to terrorism of interconnected infrastructures.” Risk Analysis, 24(6), pp. 1437–1451.
Santos, J. R., Barker, K. A., and Zelinke, P. J. (2008) “Sequential decision making in interdependent sectors with multi-objective inoperability decision trees.” Economic Systems Research, 20(1), pp. 29–56.
Santos, J. R., Orsi, Mark J., and Bond, Erik J. (2009) “Pandemic recovery analysis using the dynamic inoperability input-output model.” Risk Analysis, 29(12), pp. 1743–1758.
Simon, H. (1947) Administrative Behavior: A Study of Decision-Making Processes in Administrative Organization, The Free Press.
Society, Software Engineering Standards Committee of the IEEE Computer. (2001) IEEE Standard for Software Life Cycle processes-Risk Management, IEEE-SA Standards Board.
Srikant, R., & Agrawal, R. (1996). Mining sequential patterns: Generalizations and performance improvements (pp. 1-17). Springer Berlin Heidelberg.
Uddin, N. and Engi, D. (2002) “Disaster Management System for Southwestern Indiana.” Natural Hazards Review, 3(1), pp. 19-30.
USFDA. (2003) Disaster preparedness phases, U.S. Federal Drug Administration, Rockville MD.
Von Neumann J and Morgenstern O. (1980) Theory of Games and Economic Behavior, Princeton,. NJ: Princeton University Press.
Witten, I. H. and Frank, E. (2005). Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann.

指導教授

周建成(Chien-Cheng Chou)

審核日期

2013-9-16

推文