Advertisement

gore: Routing-Assisted Defense Against DDoS Attacks

  • Stephen T. Chou
  • Angelos Stavrou
  • John Ioannidis
  • Angelos D. Keromytis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3650)

Abstract

We present gore, a routing-assisted defense architecture against distributed denial of service (DDoS) attacks that provides guaranteed levels of access to a network under attack. Our approach uses routing to redirect all traffic destined to a customer under attack to strategically-located gore proxies, where servers filter out attack traffic and forward authorized traffic toward its intended destination.

Our architecture can be deployed incrementally by individual ISPs, does not require any collaboration between ISPs, and requires no modifications to either server- or client- software. Clients can be authorized through a web interface that screens legitimate users from outsiders or automated zombies. Authenticated clients are granted limited-time access to the network under attack. The gore architecture allows ISPs to offer DDoS defenses as a value-added service, providing necessary incentives for the deployment of such defenses. We constructed a PC-based testbed to evaluate the performance and scalability of gore. Our preliminary results show that gore is a viable approach, as its impact on the filtered traffic is minimal, in terms of both end-to-end latency and effective throughput. Furthermore, gore can easily be scaled up as needed to support larger numbers of clients and customers using inexpensive commodity PCs.

Keywords

Access Router Legitimate User Source Address Network Address Translation Border Router 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Dean, D., Franklin, M., Stubblefield, A.: An Algebraic Approach to IP Traceback. In: Proceedings of ISOC NDSS, pp. 3–12 (2001)Google Scholar
  2. 2.
    Savage, S., Wetherall, D., Karlin, A., Anderson, T.: Network Support for IP Traceback. ACM/IEEE Transactions on Networking 9, 226–237 (2001)CrossRefGoogle Scholar
  3. 3.
    Ioannidis, J., Bellovin, S.M.: Implementing Pushback: Router-Based Defense Against DDoS Attacks. In: Proceedings of ISOC NDSS (2002)Google Scholar
  4. 4.
    Cook, D.L., Morein, W.G., Keromytis, A.D., Misra, V., Rubenstein, D.: WebSOS: Protecting Web Servers From DDoS Attacks. In: Proceedings of the 11th IEEE International Conference on Networks (ICON), pp. 455–460 (2003)Google Scholar
  5. 5.
    Morein, W.G., Stavrou, A., Cook, D.L., Keromytis, A.D., Misra, V., Rubenstein, D.: Using Graphic Turing Tests to Counter Automated DDoS Attacks Against Web Servers. In: Proceedings of the 10th ACM International Conference on Computer and Communications Security (CCS), pp. 8–19 (2003)Google Scholar
  6. 6.
    von Ahn, L., Blum, M., Hopper, N.J., Langford, J.: CAPTCHA: Using Hard AI Problems For Security. In: Biham, E. (ed.) EUROCRYPT 2003. LNCS, vol. 2656, Springer, Heidelberg (2003)CrossRefGoogle Scholar
  7. 7.
    Farinacci, D., Li, T., Hanks, S., Meyer, D., Traina, P.: Generic Routing Encapsulation (GRE). RFC 2784 (2000)Google Scholar
  8. 8.
    Rigney, C., Rubens, A., Simpson, W., Willens, S.: Remote Authentication Dial In User Service (RADIUS). Request for Comments (Proposed Standard) 2138, IETF (1997) Google Scholar
  9. 9.
    Mori, G., Malik, J.: Recognizing Objects in Adversarial Clutter: Breaking a Visual CAPTCHA. In: Computer Vision and Pattern Recognition CVPR 2003 (2003)Google Scholar
  10. 10.
    Hartmeier, D.: Design and Performance of the OpenBSD Stateful Packet Filter (pf). In: Proceedings of the USENIX Technical Conference, Freenix Track (2002)Google Scholar
  11. 11.
    Goodrich, M.T.: Efficient Packet Marking for Large-Scale IP Traceback. In: Proceedings of ACM CCS, pp. 117–126 (2002)Google Scholar
  12. 12.
    Li, J., Sung, M., Xu, J., Li, L.: Large-Scale IP Traceback in High-Speed Internet: Practical Techniques and Theoretical Foundation. In: Proceedings of the IEEE Symposium on Security and Privacy (2004)Google Scholar
  13. 13.
    Snoeren, A., Partridge, C., Sanchez, L., Jones, C., Tchakountio, F., Kent, S., Strayer, W.: Hash-Based IP Traceback. In: Proceedings of ACM SIGCOMM (2001)Google Scholar
  14. 14.
    Riverhead Networks, Inc.: Centralized Protection — Riverhead Long Diversion Method Using MPLS LSP, http://www.riverhead.com/re/cprotection.pdf
  15. 15.
    Thomas, R., Mark, B., Johnson, T., Croall, J.: NetBouncer: Client-legitimacy-based Highperformance DDoS Filtering. In: Proceedings of DISCEX III, pp. 14–25 (2003)Google Scholar
  16. 16.
    Keromytis, A.D., Misra, V., Rubenstein, D.: SOS: Secure Overlay Services. In: Proceedings of ACM SIGCOMM, pp. 61–72 (2002)Google Scholar
  17. 17.
    Keromytis, A.D., Misra, V., Rubenstein, D.: SOS: An Architecture For Mitigating DDoS Attacks. IEEE Journal on Selected Areas of Communications (JSAC) 33, 413–426 (2004)Google Scholar
  18. 18.
    Ioannidis, S., Keromytis, A., Bellovin, S., Smith, J.: Implementing a Distributed Firewall. In: Proceedings of Computer and Communications Security (CCS), pp. 190–199 (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Stephen T. Chou
    • 1
  • Angelos Stavrou
    • 1
  • John Ioannidis
    • 2
  • Angelos D. Keromytis
    • 1
  1. 1.Department of Computer ScienceColumbia UniversityNew York
  2. 2.Center for Computational Learning SystemsColumbia UniversityNew York

Personalised recommendations