Worm Origin Identification Using Random Moonwalks

  • Authors:
  • Yinglian Xie;Vyas Sekar;David A. Maltz;Michael K. Reiter;Hui Zhang

  • Affiliations:
  • Carnegie Mellon University;Carnegie Mellon University;Carnegie Mellon University;Carnegie Mellon University;Carnegie Mellon University

  • Venue:
  • SP '05 Proceedings of the 2005 IEEE Symposium on Security and Privacy
  • Year:
  • 2005

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Abstract

We propose a novel technique that can determine both the host responsible for originating a propagating worm attack and the set of attack flows that make up the initial stages of the attack tree via which the worm infected successive generations of victims. We argue that knowledge of both is important for combating worms: knowledge of the origin supports law enforcement, and knowledge of the causal flows that advance the attack supports diagnosis of how network defenses were breached. Our technique exploits the "wide tree" shape of a worm propagation emanating from the source by performing random "moonwalks" backward in time along paths of flows. Correlating the repeated walks reveals the initial causal flows, thereby aiding in identifying the source. Using analysis, simulation, and experiments with real world traces, we show how the technique works against both todayýs fast propagating worms and stealthy worms that attempt to hide their attack flows among background traffic.