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FloGuard: Cost-Aware Systemwide Intrusion Defense via Online Forensics and On-Demand IDS Deployment

  • Saman Aliari Zonouz
  • Kaustubh R. Joshi
  • William H. Sanders
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6894)

Abstract

Detecting intrusions early enough can be a challenging and expensive endeavor. While intrusion detection techniques exist for many types of vulnerabilities, deploying them all to catch the small number of vulnerability exploitations that might actually exist for a given system is not cost-effective. In this paper, we present FloGuard, an on-line intrusion forensics and on-demand detector selection framework that provides systems with the ability to deploy the right detectors dynamically in a cost-effective manner when the system is threatened by an exploit. FloGuard relies on often easy-to-detect symptoms of attacks, e.g., participation in a botnet, and works backwards by iteratively deploying off-the-shelf detectors closer to the initial attack vector. The experiments using the EggDrop bot and systems with real vulnerabilities show that FloGuard can efficiently localize the attack origins even for unknown vulnerabilities, and can judiciously choose appropriate detectors to prevent them from being exploited in the future.

Keywords

Dependency Graph Intrusion Detection System Reachability Analysis Attack Scenario Forensic Analysis 
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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Saman Aliari Zonouz
    • 1
  • Kaustubh R. Joshi
    • 2
  • William H. Sanders
    • 1
  1. 1.University of IllinoisUSA
  2. 2.AT&T Labs ResearchUSA

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