Basic Approaches

  • Wolfgang Kröger
  • Enrico Zio


The two main outputs of a vulnerability assessment of critical infrastructures (CIs) are the quantification of system vulnerability indicators and the identification of critical elements


Vulnerability Assessment Finite State Machine Critical Infrastructure Probabilistic Risk Assessment Signal Flow Graph 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Albert R, Jeong H, Barabási A-L (2000) Error and attack tolerance of complex networks. Nature 406:378–382CrossRefGoogle Scholar
  2. Amaral LAN, Scala A, Barthélémy M, Stanley HE (2000) Classes of small-world networks. Proc Natl Acad Sci USA 97:11149–11152CrossRefGoogle Scholar
  3. Angel M, Werley A-K (2007) Stochastic model for power grid dynamics. In: Proceedings of the 40th Hawaii international conference on system sciences. January 3–6, 2007, Big Island, HawaiiGoogle Scholar
  4. Apostolakis E-G, Lemon M-D (2005) A screening methodology for the identification and ranking of infrastructure vulnerabilities due to terrorism. Risk Anal 25(2):361–376CrossRefGoogle Scholar
  5. Augutis J, Krikštolaitis R, Šidlauskas K, Martišauskas L, Matuziene V (2010) Modeling of energy supply disturbances in network systems. In: Briš R, Guedes Soares C, Martorell S (eds) Reliability, risk and safety: theory and applications. Taylor and Francis, LondonGoogle Scholar
  6. Billington R, Li W (1994) Reliability assessment of electric power systems using Monte Carlo methods. Plenum Press, New YorkGoogle Scholar
  7. Boccaletti S, Latora V, Moreno Y, Chavez M, Hwang D-U (2006) Complex networks: structure and dynamics. Phys Rep 424:175–308CrossRefMathSciNetGoogle Scholar
  8. Buzna L, Peters K, Ammoser H, Kühnert C, Helbing D (2007) Efficient response to cascading disaster spreading. Phys Rev E 75(5):056107CrossRefGoogle Scholar
  9. Cadini F, Zio E, Petrescu C-A (2009) Using centrality measures to rank the importance of the components of a complex network infrastructure. In: Proceedings of CRITIS’08, 13–15 October 2008, Rome, Italy, pp 155–167Google Scholar
  10. Casalicchio E, Galli E, Tucci S (2007) Federated agent-based modeling and simulation approach to study interdependencies in IT critical infrastructures. In: Proceedings of the 11th IEEE symposium on distributed simulation and real-time applications, Chania, Crete Island, GreeceGoogle Scholar
  11. Chassin P-D, Posse C (2005) Evaluating North American electric grid reliability using the Barabasi–Albert network model. Physica A 355:667–677CrossRefGoogle Scholar
  12. Chen J, Thorp S-J, Dobson I (2005) Cascading dynamics and mitigation assessment in power system disturbances via a hidden failure model. Int J Electr Power Energ Syst 27:318–326CrossRefGoogle Scholar
  13. Coffman E-G Jr, Ge Z, Misra V, Towsley D (2002) Network resilience: exploring cascading failures within BGP. In: Proceedings of the 40th annual Allerton conference on communications, computing and control, Monticello, Illinois, USAGoogle Scholar
  14. Cox D (1972) Regression models and life tables (with discussion). J R Stat Soc Ser B 34(2):187–220MATHGoogle Scholar
  15. Crucitti P, Latora V, Marchiori M (2004) Model for cascading failures in complex networks. Phys Rev E 69:045104(R)CrossRefGoogle Scholar
  16. Crucitti P, Latora V, Porta S (2006) Centrality in networks of urban streets. Chaos 16(1–9):015113CrossRefGoogle Scholar
  17. D’Inverno M, Luck M (2004) Understanding agent systems. Springer, BerlinMATHGoogle Scholar
  18. Debon A, Carrion A, Cabrera E, Solano H (2010) Comparing risk of failure models in water supply networks using ROC curves. Reliab Eng Syst Saf 95:43–48CrossRefGoogle Scholar
  19. Dekker AH (2005) Simulating network robustness for critical infrastructure networks, conferences in research and practice in information technology. In: Estivill-Castro V (ed) Proceedings of the 28th Australasian computer science conference, the University of Newcastle, vol 38. Newcastle, AustraliaGoogle Scholar
  20. Dobson I, Carreras BA, Lynch V, Newman DE (2004) Complex systems analysis of series of blackouts: cascading failure, criticality and self-organization, bulk power system dynamics and control—VI. Cortina d’Ampezzo, Italy, pp 438–451Google Scholar
  21. Dobson I, Carreras BA, Newman DE (2005) A loading-dependent model of probabilistic cascading failure. Prob Eng Inform Sci 19:15–32MATHMathSciNetGoogle Scholar
  22. Doguc O, Ramirez-Marquez EJ (2009) A generic method for estimating system reliability using Bayesian networks. Reliab Eng Syst Saf 94:542–550CrossRefGoogle Scholar
  23. Dueñas-Osorio L, Vemuru S-M (2009) Cascading failures in complex infrastructure systems. Struct Saf 31:157–167CrossRefGoogle Scholar
  24. Dueñas-Osorio L, Craig IJ, Goodno JB, Bostrom A (2007) Interdependent response of networked systems. J Infrastruct Syst 13(3):185–194CrossRefGoogle Scholar
  25. Eusgeld I, Kröger W, Sansavini G, Schläpfer M, Zio E (2009) The role of network theory and object-oriented modeling within a framework for the vulnerability analysis of critical infrastructures. Reliab Eng Syst Saf 94(5):954–963CrossRefGoogle Scholar
  26. Flammini F, Gaglione A, Mazzocca N, Pragliola C (2009) Quantitative security risk assessment and management for railway transportation infrastructures. In: Proceedings of critical information infrastructure security, third international workshop, CRITIS 2008, Rome, Italy, October 13–15, 2008. Revised papers, LNCS, Vol. 5508. Springer-Verlag, Berlin, Heidelberg, pp 180–189Google Scholar
  27. Glass JR, Beyeler EW, Stamber LK (2004) Advanced simulation for analysis of critical infrastructure: Abstract cascades, the electric power grid, and fedwire 1 (SNL paper SAND 2004-4239). Albuquerque, New Mexico 87185 and Livermore, California 94550Google Scholar
  28. Guida M, Longo M, Postiglione F (2010) Reliability analysis of next generation mobile networks. In: Briš R, Guedes Soares C, Martorell S (eds) Reliability, risk and safety: theory and applications. Taylor and Francis, LondonGoogle Scholar
  29. Hines P, Blumsack S (2008) A centrality measure for electrical networks. In: Proceedings of the 41st Hawaii international conference on system science, Big Island, HawaiiGoogle Scholar
  30. Hopkinson K, Birman K, Giovanini R, Coury D, Wang X, Thorp J (2003) EPOCHS: integrated commercial off-the-shelf software for agent-based electric power and communication simulation. In: Proceedings of the 2003 winter simulation conference, New Orleans, LA, 7–10 December 2003, pp 1158–1166Google Scholar
  31. Iyer MS, Nakayama KM, Gerbessiotis VA (2009) A Markovian dependability model with cascading failures. IEEE Trans Comput 58(9):1238–1249CrossRefMathSciNetGoogle Scholar
  32. Jeong H, Mason SP, Barabasi A-L, Oltvai ZN (2001) Lethality and centrality in protein networks. Nature 411:41–42CrossRefGoogle Scholar
  33. Johansson J, Jonsson H (2009) A model for vulnerability analysis of interdependent infrastructure networks. In: Martorell et al. (eds) Safety, reliability and risk analysis: theory, methods and applications. Proceedings of ESREL 2008 and 17th SRA Europe annual conference, Valencia, Spain, Taylor & Francis Group, London, 22–25 September 2008Google Scholar
  34. Kinney R, Crucitti P, Albert R, Latora V (2005) Modeling cascading failures in the North American power grid. Eur Phys J B 46:101–107CrossRefGoogle Scholar
  35. Kleiner Y, Rajani B (2001) Comprehensive review of structural deterioration of water mains: statistical models. Urban Water 3(3):131–150CrossRefGoogle Scholar
  36. Koonce AM, Apostolakis GE, Cook BK (2008) Bulk power risk analysis: ranking infrastructure elements according to their risk significance. Int J Electr Power Energy Syst 30:169–183CrossRefGoogle Scholar
  37. Krings A, Oman P (2002) A simple GSPN for modeling common mode failures in critical infrastructures. In: Proceedings of the 36th annual Hawaii international conference on system sciences (HICSS’03), Big Island, HawaiiGoogle Scholar
  38. Langeron Y, Barros A, Grall A, Bérenguer C (2010) Reliability assessment of network-based safety-related systems. In: Briš R, Guedes Soares C, Martorell S (eds) Reliability, risk and safety: theory and applications. Taylor and Francis, LondonGoogle Scholar
  39. Laprie J-C, Kanoun K, Kaâniche M (2007) Modelling interdependencies between the electricity and information infrastructures. In: Proceedings of the 26th international conference on computer safety, reliability, and security (SAFECOMP 2007), Nuremberg, Germany, LNCS 4680/2009Google Scholar
  40. Latora V, Marchiori M (2001) Efficient behavior of small-world networks. Phys Rev Lett 87(19):198701 (1–4)CrossRefGoogle Scholar
  41. Latora V, Marchoiri M (2005) Vulnerability and protection of infrastructure networks. Phys Rev E 71:015103 (1–4)CrossRefGoogle Scholar
  42. Lord D, Washington PS, Ivan NJ (2005) Poisson, Poisson-gamma and zero inflated regression models of motor vehicle crashes: balancing statistical fit and theory. Accid Anal Prev 37:35–46CrossRefGoogle Scholar
  43. Luck M, McBurney P, Preist C (2003) Agent technology: enabling next generation computing (A roadmap for agent based computing). AgentLink II. University of Southampton, Southampton, UKGoogle Scholar
  44. Marseguerra M, Zio E (2002) Basics of the Monte Carlo method with application to system reliability. LiLoLe-Verlag GmbH, Hagen, GermanyGoogle Scholar
  45. McCullagh P, Nelder J (1989) Generalized linear models. Chapman & Hall, LondonMATHGoogle Scholar
  46. MIA (2010) Definition of a methodology for the assessment of mutual interdependencies between ICT and electricity generation/transmission infrastructures. Final report, September 2010, Italian National Agency for New Technology, Energy and Environment, ItalyGoogle Scholar
  47. Moore AD (2006) Application of the API/NPRA SVA methodology to transportation security issues. J Hazard Mater 130:107–121CrossRefGoogle Scholar
  48. Morgan MG, Florig HK, DeKay ML, Fischbeck P (2000) Categorizing risks for risk ranking. Risk Anal 20:49–58CrossRefGoogle Scholar
  49. Motter A-E (2004) Cascade control and defense in complex networks. Phys Rev Lett 93(9):098701(1-4)CrossRefGoogle Scholar
  50. Motter A-E, Lai Y-C (2002) Cascade-based attacks on complex networks. Phys Rev E 66(1–4):065102Google Scholar
  51. Newman D-E, Nkei B, Carreras BA, Dobson I, Lynch VE, Gradney P (2005) Risk assessment in complex interacting infrastructure systems. In: Proceedings of the 38th Hawaii international conference on system sciences, Big Island, HawaiiGoogle Scholar
  52. Panzieri S, Setolaand R, Ulivi G (2004) An agent based simulator for critical interdependent infrastructures. In: Proceedings of the 2nd international conference on critical infrastructures CRIS2004: October 25–27, 2004, Grenoble, FranceGoogle Scholar
  53. Paté-Cornell ME, Guikema SD (2002) Probabilistic modeling of terrorist threats: a systems analysis approach to setting priorities among countermeasures. Mil Oper Res 7(3):5–23Google Scholar
  54. Piwowar J, Chatelet E, Laclemence P (2009) An efficient process to reduce infrastructure vulnerabilities facing malevolence. Reliab Eng Syst Saf 94:1869–1877CrossRefGoogle Scholar
  55. Rosato V, Bologna S, Tiriticco F (2007) Topological properties of high-voltage electrical transmission networks. Electr Pow Syst Res 77:99–105CrossRefGoogle Scholar
  56. Schläpfer M, Kessler T, Kröger W (2008) Reliability analysis of electric power systems using an object-oriented hybrid modeling approach. In: Proceedings of the 16th power systems computation conference, GlasgowGoogle Scholar
  57. Strogatz SH (2001) Exploring complex networks. Nature 410:268–276CrossRefGoogle Scholar
  58. Sultana S, Chen Z (2009) Modeling flood induced interdependencies among hydroelectricity generating infrastructures. J Environ Manage 90:3272–3282CrossRefGoogle Scholar
  59. Watts D-J (2002) A simple model of global cascades on random networks. Proc Natl Acad Sci USA 99(9):5766–5771MATHCrossRefMathSciNetGoogle Scholar
  60. Watts D-J, Strogatz SH (1998) Collective dynamics of ‘small-world’ networks. Nature 39:440–442CrossRefGoogle Scholar
  61. Yamijala S, Guikema DS, Brumbelow K (2009) Statistical models for the analysis of water distribution system pipe break data. Reliab Eng Syst Saf 94:282–293CrossRefGoogle Scholar
  62. Zimmerman R (2001) Social implications of infrastructure network interactions. J Urban Technol 8(3):97–119CrossRefGoogle Scholar
  63. Zio E, Sansavini G (2008) Modeling failure cascades in networks systems due to distributed random disturbances and targeted intentional attacks. In: Martorell et al. (eds) Safety, reliability and risk analysis: theory, methods and applications. Proceedings of ESREL 2008 and 17th SRA Europe annual conference, 22–25 September 2008, Valencia, Spain, Taylor & Francis Group, LondonGoogle Scholar
  64. Zio E, Sansavini G (2011a) Component criticality in failure cascade processes of network systems. Risk Anal. doi: 10.1111/j.1539-6924.2011.01584.x
  65. Zio E, Sansavini G (2011b) Modeling interdependent network systems for identifying cascade-safe operating margins. IEEE Trans Reliab 60(1):94–101CrossRefGoogle Scholar
  66. Zio E, Sansavini G, Maja R, Marchionni G (2008) An analytical approach to the safety of road networks. Int J Reliab Qual Saf Eng 15(1):67–76CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Limited  2011

Authors and Affiliations

  1. 1.Mechanical and Process Engineering DepartmentETH ZurichZurichSwitzerland
  2. 2.Ecole Centrale Paris, Laboratoire Génie IndustrielChatenay-Malabry CedexFrance

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