An Efficient Distributed Algorithm to Identify and Traceback DDoS Traffic

  • Authors:
  • T. Y. Wong;K. T. Law;John C. S. Lui;M. H. Wong

  • Affiliations:
  • *Corresponding author: tywong@cse.cuhk.edu.hk;Department of Computer Science and Engineering, The Chinese University of Hong Kong Hong Kong;Department of Computer Science and Engineering, The Chinese University of Hong Kong Hong Kong;Department of Computer Science and Engineering, The Chinese University of Hong Kong Hong Kong

  • Venue:
  • The Computer Journal
  • Year:
  • 2006

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Abstract

Distributed denial-of-service attack is one of the most pressing security problems that the Internet community needs to address. Two major requirements for effective traceback are (i) to quickly and accurately locate potential attackers and (ii) to filter attack packets so that a host can resume the normal service to legitimate clients. Most of the existing IP traceback techniques focus on tracking the location of attackers after-the-fact. In this work, we provide an efficient methodology for locating potential attackers who employ the flood-based attack. We propose a distributed algorithm so that a set of routers can correctly (in a distributed sense) gather statistics in a coordinated fashion and that a victim site can deduce the local traffic intensities of all these participating routers. We prove the correctness of our distributed algorithm, and given the collected statistics, we provide a method for the victim site to locate attackers who sent out dominating flows of packets. The proposed distributed traceback methodology can also complement and leverage on the existing ICMP traceback so that a more efficient and accurate traceback can be obtained. We carry out simulations to illustrate that the proposed methodology can locate the attackers in a short period of time. Moreover, the applications as well as the limitations of the proposed methodology are covered. We believe this work also provides the theoretical foundation on how to correctly and accurately perform distributed measurement and traffic estimation on the Internet.