Privacy Attack Modeling and Risk Assessment Method for Name Data Networking

  • Vishwa Pratap SinghEmail author
  • R. L. Ujjwal
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 924)


Assessment of security threat for Internet has become a major concern because of the advancement and expansion of IT in recent years, and it is equally important for future Internet architectures. Name data networking architecture is designed from scratch and is immune to most of the security attacks that are common in IP-based networks. The newly added features give rise to new security attacks which can compromise user privacy, data confidentiality, and integrity. Formal mathematical modeling is essential for proper assessments and mitigation from the security attacks. Security attack modeling provides insight of network vulnerabilities and helps in identifying the areas, which have to be kept on priority. This paper presents an attack tree-based privacy attack modeling and risk assessment technique for NDN. First attack tree is constructed in a top-down approach to find out possible attacks and threats that compromise user privacy from the attacker’s point of view and then presented risk assessment technique to ascertain degree of threat that an attack imposes on user privacy.


NDN Risk assessment Attack tree Attack modeling 


  1. 1.
    Zhang, L., Estrin, D., Burke, J., Jacobson, V., Thornton, J.D., Smetters, D.K., Zhang, B., Tsudik, G., Massey, D., Papadopoulos, C.: Named data networking (ndn) project. Relatório Técnico NDN-0001, Xerox Palo Alto Research Center-PARC 15, 158 (2010)Google Scholar
  2. 2.
    Zhang, L., Afanasyev, A., Burke, J., Jacobson, V., Crowley, P., Papadopoulos, C., Wang, L., Zhang, B.: Named data networking. ACM SIGCOMM Comput. Commun. Rev. 44(3), 66–73 (2014)CrossRefGoogle Scholar
  3. 3.
    Chen, S., Mizero, F.: A survey on security in named data networking. arXiv preprint arXiv:1512.04127 (2015)
  4. 4.
    Yi, C., Afanasyev, A., Moiseenko, I., Wang, L., Zhang, B., Zhang, L.: A case for stateful forwarding plane. Comput. Commun. 36(7), 779–791 (2013)CrossRefGoogle Scholar
  5. 5.
    Dai, H.: Mitigate ddos attacks in ndn by interest traceback. In: 2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). IEEE (2013)Google Scholar
  6. 6.
    Conti, M., Gasti, P., Teoli, M.: A lightweight mechanism for detection of cache pollution attacks in named data networking. Comput. Netw. 57(16), 3178–3191 (2013)CrossRefGoogle Scholar
  7. 7.
    Wu, D., Xu, Z., Chen, B., Zhang, Y.: What if routers are malicious? mitigating content poisoning attack in ndn. In: Trustcom/BigDataSE/I200B SPA, 2016 IEEE 2016 Aug 23 (pp. 481–488). IEEEGoogle Scholar
  8. 8.
    Mauw, S., Oostdijk, M.: Foundations of attack trees. In: International Conference on Information Security and Cryptology. Springer, Berlin, Heidelberg (2005)Google Scholar
  9. 9.
    Schneier, B.: Attack trees. Dr. Dobb’s J. 24(12), 21–29 (1999)Google Scholar
  10. 10.
    Amadeo, M., Campolo, C., Molinaro, A.: Forwarding strategies in named data wireless ad hoc networks: design and evaluation. J. Netw. Comput. Appl. 1(50), 148–158 (2015)CrossRefGoogle Scholar
  11. 11.
    Singh, A.K., Mohan, A.: Computation of probability coefficients using binary decision diagram and their application in test vector generation. Int. J. Comput. Sci. Eng. 3(1), 33–40 (2009)Google Scholar
  12. 12.
    Hand, R.S.: Toward an active network security architectureGoogle Scholar
  13. 13.
    Tourani, R., Mick, T., Misra, S., Panwar, G.: Security, privacy, and access control in information-centric networking: a survey. arXiv preprint arXiv:1603.03409, 10 Mar 2016
  14. 14.
    Vasilakos, A.: Information centric network: research challenges and opportunities. J. Netw. Comput. Appl. 52, 1–10 (2015)CrossRefGoogle Scholar
  15. 15.
    Bagnato, A.: Attribute decoration of attack–defense trees. Int. J. Secure Softw. Eng. 3(2), 1–35 (2012)MathSciNetCrossRefGoogle Scholar
  16. 16.
    Hu, N., Steenkiste, P.: Evaluation and characterization of available bandwidth probing techniques. IEEE J. Sel. Areas Commun. 21(6), 879–894 (2003)CrossRefGoogle Scholar
  17. 17.
    Mateo, San Cristóbal, J.R.: Multi-attribute utility theory. In: Multi Criteria Analysis in the Renewable Energy Industry. Springer, London, pp. 63–72 (2012)CrossRefGoogle Scholar
  18. 18.
    Akers, S.B.: Binary decision diagrams. IEEE Trans. Comput. 6, 509 (1978)CrossRefzbMATHGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Guru Gobind Singh Indraprastha UniversityNew DelhiIndia

Personalised recommendations