Vulnerability Analysis of High Dimensional Complex Systems

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6366)


Complex systems experience dramatic changes in behavior and can undergo transitions from functional to dysfunctional states. An unstable system is prone to dysfunctional collective cascades that result from self-reinforcing behaviors within the system. Because many human and technological civilian and military systems today are complex systems, understanding their susceptibility to collective failure is a critical problem. Understanding vulnerability in complex systems requires an approach that characterizes the coupled behaviors at multiple scales of cascading failures. We used neuromorphic methods, which are modeled on the pattern-recognition circuitry of the brain and can find patterns in high-dimensional data at multiple scales, to develop a procedure for identifying the vulnerabilities of complex systems. This procedure was tested on microdynamic Internet2 network data. The result was a generic pipeline for identifying extreme events in high dimensional datasets.


Data Stream Extreme Event Kernel Principal Component Analysis Vulnerability Analysis Border Gateway Protocol 
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.


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  1. 1.
    B.G.P.: routing table analysis, (modified August 2006)
  2. 2.
    BGPmon: Next generation BGP Monitor,
  3. 3.
    Border gateway protocol (BGP) data collection standard communities, (modified February 23, 2006)
  4. 4.
    New sources of BGP data, (modified October 28, 2008)
  5. 5.
    University of Oregon Route Views Project, (modified January 25, 2005)
  6. 6.
    Adam, C., Stadler, R.: Patterns for routing and self-stabilization. In: Proc IEEE/IFPS NOMS (2004)Google Scholar
  7. 7.
    Bar-Yam, Y.: Multiscale complexity/entropy. Advances in Complex Systems 7, 47–63Google Scholar
  8. 8.
    Bar-Yam, Y.: Multiscale variety in complex systems. Complexity 9(4), 37–45 (2004)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Bar-Yam, Y.: Dynamics of Complex Systems. Perseus Press, Cambridge (1997)zbMATHGoogle Scholar
  10. 10.
    Barabási, A.L., de Menezes, M., Balensiefer, S., Brockman, J.: Hot spots and universality in network dynamics. The European Physical Journal B 38, 169–175 (2004)CrossRefGoogle Scholar
  11. 11.
    Cowie, J., Ogielski, A., Premore, B., Yuan, Y.: Global routing instabilities triggered by Code Red II and Nimda worm attacksGoogle Scholar
  12. 12.
    Cowie, J., Ogielski, A., Premore, B., Yuan, Y.: Internet worms and global routing instabilities: scalability and traffic control in IP networks II. In: Proc SPIE, vol. 4868, pp. 195–199 (2002)Google Scholar
  13. 13.
    Cymru, T.: BGP monitoring, (modified 2010)
  14. 14.
    Dolev, S.: Self-stabilization. MIT Press, Cambridge (2000)zbMATHGoogle Scholar
  15. 15.
    Gheorghiu-Svirchevski, S., Bar-Yam, Y.: Multiscale analysis of information correlations in an infinite-range, ferromagnetic ising system. Phys. Rev. E 70(066115) (2004)Google Scholar
  16. 16.
    Hohn, N.: Measuring, understanding, and modelling internet trafficGoogle Scholar
  17. 17.
    Huberman, B., Lukose, R.: Social dilemmas and internet congestion. Science 277 (1997)Google Scholar
  18. 18.
  19. 19.
    Izenman, A.: Modern Multivariate Statistical Techniques. Springer, Heidelberg (2008)CrossRefzbMATHGoogle Scholar
  20. 20.
    Coffman Jr., E.G., Ge, Z., Misra, V., Towsley, D.: Network resilience: exploring cascading failures within bgp. In: Proceedings of Allerton Conference on Communications, Computing, and Control (2001)Google Scholar
  21. 21.
    Labovitz, C., Malan, G., Jahanian, F.: Internet routing instability 6(5) (1998)Google Scholar
  22. 22.
    Lakhina, A., Crovella, M., Diot, C.: Mining anomalies using traffic feature distributions. BUCS (002) (2005)Google Scholar
  23. 23.
  24. 24.
    Mao, Z., Govindan, R., Varghese, G., Katz, R.: Route flap damping exacerbates internet routing convergence. In: Proceedings of ACM SIGCOMM, Pittsburgh, PA, USA, pp. 221–233 (2002)Google Scholar
  25. 25.
    de Menezes, M., Barabási, A.L.: Fluctuations in network dynamics. Phys. Rev. Lett. 92(028701) (2008)Google Scholar
  26. 26.
    Metzler, R., Bar-Yam, Y.: Multiscale analysis of correlated gaussians. Phys. Rev. E 71(046114), 2005 (2005)Google Scholar
  27. 27.
    Metzler, R., Bar-Yam, Y., Kardar, M.: Information flow through a chaotic channel: prediction and postdiction at finite resolution. Phys. Rev. E 70(020605) (2004)Google Scholar
  28. 28.
    Misra, V., Harmon, D., de Aguiar, M., Epstein, I., Braha, D., Bar-Yam, Y.: Vulnerability detection in complex systems. Unpublished report (2009)Google Scholar
  29. 29.
    Motter, A., Lai, Y.C.: Cascade-based attacks on complex networks. Phys. Rev. E 66(065102) (2002)Google Scholar
  30. 30.
    Nicol, D.: Challenges in using simulation to explain global routing instabilities. In: Conference on Grand Challenges in Simulation (2002)Google Scholar
  31. 31.
    Perlman, R.: Interconnections: Bridges, Routers, Switches and Internetworking Protocols, 2nd edn. Addison-Wesley Longman, Amsterdam (2001)Google Scholar
  32. 32.
    Valverde, S., Solé, R.: Internet’s critical path horizon. The European Physical Journal B 38(2) (2004)Google Scholar
  33. 33.
    Siganos, G., Faloutsos, M.: Detection of BGP routing misbehavior against cyber-terrorism. In: IEEE Military Communications Conference (2005)Google Scholar
  34. 34.
    Smith, R.: The dynamics of internet traffic: self-similarity, self-organization, and complex phenomena. ArXiV:0806.3374 (2008)Google Scholar
  35. 35.
    Wang, L., Zhao, X., Pei, D., Bush, R., Massey, D., Mankin, A., Wu, S., Zhang, L.: Observation and analysis of BGP behavior under stress. In: Proceedings of the 2nd ACM SIGCOMM workshop of internet measurement (2002)Google Scholar
  36. 36.
    Wang, Y.: Protecting mission critical networks. Seminar on Network Security Publications in Telecommunications Software and Multimedia (2001)Google Scholar
  37. 37.
    Yuan, J., Mills, K.: Macroscopic dynamics in large-scale data networks. Complex Dynamics in Communication Networks (2005)Google Scholar
  38. 38.
    Zou, C.C., Gong, W., Towsley, D.: Code red worm propagation modeling and analysis. In: Proceedings of the 9th ACM conference on Computer and communications security (2002)Google Scholar
  39. 39.
    Zou, C., Gao, L., Gong, W., Towsley, D.: Monitoring and early warning for internet worms. In: Proceedings of the 10th ACM conference on Computer and communications security (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.New England Complex Systems InstituteUSA

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