, Volume 57, Issue 1, pp 82–96 | Cite as

Secure Overlay Network Design

  • Li (Erran) Li
  • Mohammad Mahdian
  • Vahab S. Mirrokni


Due to the increasing security threats on the Internet, new overlay network architectures have been proposed to secure privileged services. In these architectures, the application servers are protected by a defense perimeter where only traffic from entities called servlets are allowed to pass. End users must be authorized and can only communicate with entities called access points (APs). APs relay authorized users’ requests to servlets, which in turn pass them to the servers. The identity of APs are publicly known while the servlets are typically secret. All communications are done through the public Internet. Thus all the entities involved form an overlay network. The main component of this distributed system consists of n APs and m servlets. A design for a network is a bipartite graph with APs on one side, and the servlets on the other side. If an AP is compromised by an attacker (or fails), all the servlets that are connected to it are subject to attack. An AP is blocked, if all servlets connected to it are subject to attack. We consider two models for the failures: In the stochastic model, we assume that each AP i fails with a given probability p i . In the adversarial model, we assume that there is an adversary that knows the topology of the network and chooses at most k APs to compromise. In both models, our objective is to design the connections between APs and servlets to minimize the (expected/worst-case) number of blocked APs. In this paper, we give a polynomial-time algorithm for this problem in the stochastic model when the number of servlets is a constant. We also show that if the probability of failure of each AP is at least 1/2, then in the optimal design each AP is connected to only one servlet (we call such designs star-shaped), and give a polynomial-time algorithm to find the best star-shaped design. We observe that this statement is not true if the failure probabilities are small. In the adversarial model, we show that the problem is related to a problem in combinatorial set theory, and use this connection to give bounds on the maximum number of APs that a perfectly failure-resistant design with a given number of servlets can support. Our results provide the first rigorous theoretical foundation for practical secure overlay network design.


Network design Network security Optimization Combinatorics 


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  1. 1.
    Adler, M.: Tradeoffs in probabilistic packet marking for IP traceback. In: Proc. ACM Symposium on Theory of Computing (STOC), May, pp. 407–418 (2002) Google Scholar
  2. 2.
    Bu, T., Norden, S., Woo, T.: Trading resiliency for security: Model and algorithms. In: Proc. IEEE International Conference on Network Protocols (ICNP), pp. 218–227 (2004) Google Scholar
  3. 3.
    Burch, H., Cheswick, B.: Tracing anonymous packets to their approximate source. In: Proc. USENIX LISA, December, pp. 319–327 (2000) Google Scholar
  4. 4.
    Dean, D., Franklin, M., Stubblefield, A.: An algebraic approach to IP traceback. In: Proc. Network and Distributed System Security Symposium (NDSS), February, pp. 3–12 (2001) Google Scholar
  5. 5.
    Doeppner, T., Klein, P., Koyfman, A.: Using router stamping to identify the source of IP packets. In: Proc. ACM Conference on Computer and Communications Security (CCS), November, pp. 184–189 (2000) Google Scholar
  6. 6.
    Ferguson, P.: Network ingress filtering: Defeating denial of service attacks which employ IP source address spoofing. RFC 2267, January (1998) Google Scholar
  7. 7.
    Garber, L.: Denial-of-service attacks rip the Internet. IEEE Comput. 33(4), 12–17 (2000) Google Scholar
  8. 8.
    Goodrich, M.T.: Efficient packet marking for large-scale IP traceback. In: Proc. ACM Conference on Computer and Communications Security (CCS), November, pp. 117–126 (2002) Google Scholar
  9. 9.
    Keromytis, A.D., Misra, V., Rubenstein, D.: SOS: Secure overlay services. In: Proc. ACM SIGCOMM, August, pp. 61–72 (2002) Google Scholar
  10. 10.
    Kleitman, D., Spencer, J.: Families of k-independent sets. Discrete Math. 6, 255–262 (1973) MATHCrossRefMathSciNetGoogle Scholar
  11. 11.
    Li, J., Sung, M., Xu, J., Li, L.E.: Large-scale IP traceback in high-speed Internet: Practical techniques and theoretical foundation. In: Proc. IEEE Symposium on Security and Privacy, pp. 115–129 (2004) Google Scholar
  12. 12.
    Li, L., Mahdian, M., Mirrokni, V.: Secure overlay network design. In: Proceedings of the 2nd International Conference on Algorithmic Aspects in Information and Management (AAIM). Lecture Notes in Computer Science, vol. 4041, pp. 354–366. Springer, Berlin (2006) CrossRefGoogle Scholar
  13. 13.
    Mahajan, R., Bellovin, S., Floyd, S., Ioannidis, J., Paxson, V., Shenker, S.: Controlling high bandwidth aggregates in the network. ACM Comput. Commun. Rev. 32(3), 62–73 (2002) CrossRefGoogle Scholar
  14. 14.
    McGuire, D., Krebs, B.: Attack on Internet called largest ever., October (2002)
  15. 15.
    Mirkovic, J., Prier, G., Reiher, P.: Attacking DDoS at the source. In: Proc. IEEE International Conference on Network Protocols (ICNP), November, pp. 312–321 (2002) Google Scholar
  16. 16.
    Papadopoulos, C., Lindell, R., Mehringer, J., Hussain, A., Govidan, R.: COSSACK: coordinated suppression of simultaneous attacks. In: DISCEX III, April, pp. 22–24 (2003) Google Scholar
  17. 17.
    Park, K., Lee, H.: On the effectiveness of route-based packet filtering for distributed DoS attack prevention in power-law Internets. In: Proc. ACM SIGCOMM, August, pp. 15–26 (2001) Google Scholar
  18. 18.
    Provan, J.S., Ball, M.O.: The complexity of counting cuts and of computing the probability that a graph is connected. SIAM J. Comput. 12(4), 777–788 (1983) MATHCrossRefMathSciNetGoogle Scholar
  19. 19.
    Ruszinkó, M.: On the upper bound of the size of the r-cover-free families. J. Comb. Theory Ser. A 66, 302–310 (1994) MATHCrossRefGoogle Scholar
  20. 20.
    Savage, S., Wetherall, D., Karlin, A., Anderson, T.: Practical network support for IP traceback. In: Proc. ACM SIGCOMM, August, pp. 295–306 (2000) Google Scholar
  21. 21.
    Snoeren, A., Partridge, C., et al.: Hash-based IP traceback. In: Proc. ACM SIGCOMM, August, pp. 3–14 (2001) Google Scholar
  22. 22.
    Song, D., Perrig, A.: Advanced and authenticated marking schemes for IP traceback. In: Proc. IEEE INFOCOM, April, pp. 878–886 (2001) Google Scholar
  23. 23.
    van Lint, J.H., Wilson, R.M.: A Course in Combinatorics. Cambridge University Press, Cambridge (2001) MATHGoogle Scholar
  24. 24.
    Vijayan, J.: Akamai attack reveals increased sophistication: Host’s DNS servers were DDoS targets, slowing large sites.,10801,93977p2,00.html, June (2004)

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Li (Erran) Li
    • 1
  • Mohammad Mahdian
    • 2
  • Vahab S. Mirrokni
    • 3
  1. 1.Bell LaboratoriesMurray HillUSA
  2. 2.Yahoo! ResearchSanta ClaraUSA
  3. 3.Microsoft ResearchRedmondUSA

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