Paper
15 September 2004 Rapid detection of worms using ICMP-T3 analysis
Author Affiliations +
Abstract
Identification of an active Internet worm is a manual process where security analysts must observe and analyze unusual activity on multiple firewalls, intrusion-detection systems or hosts. A worm might not be positively identified until it already has spread to most of the Internet, eliminating many defensive options. In previous work, we developed an automated system that can identify active worms seconds or minutes after they first begin to spread, a necessary precursor to halting the spread of the worm rather than simply cleaning up afterward. The system collects ICMP Destination Unreachable messages from instrumented network routers, identifies those patterns of unreachable messages that indicate malicious scanning activity, and then searches for patterns of scanning activity that indicate a propagating worm. In this paper, we compare the performance of two different detection strategies, our previous threshold approach and a new line-fit approach, for different worm-propagation techniques, noise environments, and system parameters. These techniques work for worms that generate at least some of their target addresses through a random process, a feature of most recent worms. Although both being powerful methods for fast worm identification, the new line-fit approach proves to be significantly more noise resistant.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert S. Gray and Vincent H. Berk "Rapid detection of worms using ICMP-T3 analysis", Proc. SPIE 5403, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense III, (15 September 2004); https://doi.org/10.1117/12.548171
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CITATIONS
Cited by 8 scholarly publications.
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KEYWORDS
Data modeling

Internet

Performance modeling

Stochastic processes

Homeland security

Instrument modeling

Process modeling

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