Vulnerability Against Internet Disruptions – A Graph-Based Perspective

  • Annika BaumannEmail author
  • Benjamin Fabian
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9578)


The Internet of today permeates societies and markets as a critical infrastructure. Dramatic network incidents have already happened in history with strong negative economic impacts. Therefore, assessing the vulnerability of Internet connections against failures, accidents and malicious attacks is an important field of high practical relevance. Based on a large integrated dataset describing the Internet as a complex graph, this paper develops a multi-dimensional Connectivity Risk Score that, to our knowledge, constitutes the first proposal for a topological connectivity-risk indicator of single Autonomous Systems, the organizational units of the Internet backbone. This score encompasses a variety of topological robustness metrics and can help risk managers to assess the vulnerability of their organizations even beyond network perimeters. Such analyses can be conducted in a user-friendly way with the help of CORIA, a newly developed software framework for connectivity risk analysis. Our approach can serve as an important element in an encompassing strategy to assess and improve companies’ connectivity to the Internet.


Vulnerability Internet robustness Internet topology Graph mining Risk score 


  1. 1.
    CDW. Billions Lost due to IT Network Outages in 2010: Survey (2011). Accessed 30 Apr 2015
  2. 2.
    Baumann, A., Fabian, B.: Who runs the internet? Classifying autonomous systems into industries. In: Proceedings of the 10th International Conference on Web Information Systems and Technologies (WEBIST), Barcelona, Spain (2014)Google Scholar
  3. 3.
    Tseng, J.C., Wu, C.-H.: An expert system approach to improving stability and reliability of web service. Expert Syst. Appl. 33(2), 379–388 (2007)CrossRefGoogle Scholar
  4. 4.
    Baumann, A., Fabian, B.: How robust is the internet? – Insights from graph analysis. In: Lopez, J., Ray, I., Crispo, B. (eds.) CRiSIS 2014. LNCS, vol. 8924, pp. 247–254. Springer, Heidelberg (2015)Google Scholar
  5. 5.
    Albert, R., Jeong, H., Barabási, A.-L.: Error and attack tolerance of complex networks. Nature 406, 378–382 (2000)CrossRefGoogle Scholar
  6. 6.
    Dolev, D., Jamin, S., Mokryn, O., Shavitt, Y.: Internet resiliency to attacks and failures under BGP policy routing. Comput. Netw. 50(16), 3183–3196 (2006)CrossRefzbMATHGoogle Scholar
  7. 7.
    Wu, J., Zhang, Y., Morley Mao, Z., Shin, K.G.: Internet routing resilience to failures: analysis and implications. In: Proceedings of 2007 ACM CoNEXT Conference (CoNEXT 2007), New York, NY, USA (2007)Google Scholar
  8. 8.
    Xiao, S., Xiao, G., Cheng, T.H.: Tolerance of intentional attacks in complex communication networks. IEEE Commun. Mag. 46(1), 146–152 (2008)CrossRefGoogle Scholar
  9. 9.
    Deng, W., Karaliopoulos, M., Mühlbauer, W., Zhu, P., Lu, X., Plattner, B.: k-fault tolerance of the internet AS graph. Comput. Netw. 55(10), 2492–2503 (2011)CrossRefGoogle Scholar
  10. 10.
    Zhao, J., Wu, J., Chen, M., Fang, Z., Xu, K.: K-core-preferred attack to the internet: is it more malicious than degree attack? In: Wang, J., Xiong, H., Ishikawa, Y., Xu, J., Zhou, J. (eds.) WAIM 2013. LNCS, vol. 7923, pp. 717–728. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  11. 11.
    Çetinkaya, E.K., Broyles, D., Dandekar, A., Srinivasan, S., Sterbenz, J.P.: Modelling communication network challenges for future internet resilience, survivability, and disruption tolerance: a simulation-based approach. Telecommun. Syst. 52(2), 751–766 (2013)Google Scholar
  12. 12.
    Shirazi, F., Diaz, C., Mullan, C., Wright, J., Buchmann, J.: Towards measuring resilience in anonymous communication networks. In: Proceedings of 6th Hot Topics in Privacy Enhancing Technologies (HotPETs 2013) (2013)Google Scholar
  13. 13.
    CAIDA AS Rank (2014). AS Ranking. Accessed 30 Apr 2015
  14. 14.
    UCLA (2014). Accessed 30 Apr 2015
  15. 15.
    CAIDA Ark (2014). Archipelago Measurement Infrastructure. Accessed 30 Apr 2015
  16. 16. (2014). Internet Routing Registry. Accessed 30 Apr 2015
  17. 17.
    Siganos, G., Faloutsos, M.: Detection of BGP routing misbehavior against cyber-terrorism. In: Proceedings of the 2005 IEEE Military Communications Conference (MILCOM 2005), pp. 923–929 (2005)Google Scholar
  18. 18.
    Zhang, B., Liu, R., Massey, D., Zhang, L.: Collecting the internet AS-level topology. ACM SIGCOMM Comput. Commun. Rev. 35(1), 53–61 (2005)CrossRefGoogle Scholar
  19. 19.
    Mahadevan, P., Krioukov, D., Fomenkov, M., Huffaker, B., Dimitropoulos, X., Claffy, K., Vahdat, A.: The internet AS-level topology: three data sources and one definitive metric. ACM SIGCOMM Comput. Commun. Rev. (CCR) 36(1), 17–26 (2006)Google Scholar
  20. 20.
    Manzano, M., Calle, E., Harle, D.: Quantitative and qualitative network robustness analysis under different multiple failure scenarios. In: Proceedings of the 3rd International Congress on Ultra Modern Telecommunications and Control Systems and Workshops, pp. 1–7 (2011)Google Scholar
  21. 21.
    NetworkX (2014). Accessed 30 Apr 2015
  22. 22.
    Redis (2014). Accessed 30 Apr 2015
  23. 23.
    Sinatra (2014). Accessed 30 Apr 2015
  24. 24.
    Twitter Bootstrap (2014). Twitter Bootstrap Library. Accessed 30 Apr 2015
  25. 25.
    Lin, Y.-K., Chang, P.-C.: Maintenance reliability estimation for a cloud computing network with nodes failure. Expert Syst. Appl. 38(11), 14185–14189 (2011)MathSciNetGoogle Scholar
  26. 26.
    Sterbenz, J.P.G., Hutchison, D., Çetinkaya, E.K., Jabbar, A., Rohrer, J.P., Schöller, M., Smith, P.: Resilience and survivability in communication networks: strategies, principles, and survey of disciplines. Comput. Netw. 54(8), 1245–1265 (2010)CrossRefzbMATHGoogle Scholar
  27. 27.
    Wang, Y., Chakrabarti, D., Wang, C., Faloutsos, C.: Epidemic spreading in real networks: an eigenvalue viewpoint. In: International Symposium on Reliable Distributed Systems, pp. 25–34 (2003)Google Scholar
  28. 28.
    D’Agostino, G., Scala, A., Zlatić, V., Caldarelli, G.: Robustness and assortativity for diffusion-like processes in scale-free networks. EPL (Europhysics Letters) 97(6), 68006 (2012)CrossRefGoogle Scholar
  29. 29.
    Van Mieghem, P., Doerr, C., Wang, H., Hernandez, J.M., Hutchison, D., Karaliopoulos, M., Kooij, R.E.: A framework for computing topological network robustness. Delft University of Technology (2010)Google Scholar
  30. 30.
    ResumeNet (2011). Accessed 14 Aug 2015
  31. 31.
    Fabian, B., Baumann, A., Lackner, J.: Topological analysis of cloud service connectivity. Comput. Ind. Eng. 88, 151–165 (2015)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Institute of Information SystemsHumboldt-Universität zu BerlinBerlinGermany

Personalised recommendations