A Host-Based Approach for Unknown Fast-Spreading Worm Detection and Containment

  • Authors:
  • Songqing Chen;Lei Liu;Xinyuan Wang;Xinwen Zhang;Zhao Zhang

  • Affiliations:
  • George Mason University;George Mason University;George Mason University;Samsung Information Systems America;Iowa State University

  • Venue:
  • ACM Transactions on Autonomous and Adaptive Systems (TAAS) - Special Section on Best Papers from SEAMS 2012
  • Year:
  • 2014

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Abstract

The fast-spreading worm, which immediately propagates itself after a successful infection, is becoming one of the most serious threats to today’s networked information systems. In this article, we present WormTerminator, a host-based solution for fast Internet worm detection and containment with the assistance of virtual machine techniques based on the fast-worm defining characteristic. In WormTerminator, a virtual machine cloning the host OS runs in parallel to the host OS. Thus, the virtual machine has the same set of vulnerabilities as the host. Any outgoing traffic from the host is diverted through the virtual machine. If the outgoing traffic from the host is for fast worm propagation, the virtual machine should be infected and will exhibit worm propagation pattern very quickly because a fast-spreading worm will start to propagate as soon as it successfully infects a host. To prove the concept, we have implemented a prototype of WormTerminator and have examined its effectiveness against the real Internet worm Linux/Slapper. Our empirical results confirm that WormTerminator is able to completely contain worm propagation in real-time without blocking any non-worm traffic. The major performance cost of WormTerminator is a one-time delay to the start of each outgoing normal connection for worm detection. To reduce the performance overhead, caching is utilized, through which WormTerminator will delay no more than 6% normal outgoing traffic for such detection on average.