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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Perdisci, R. Dagon, D. Wenke Lee Fogla, P. Sharif, M. |
| Copyright Year | 2006 |
| Description | Author affiliation: Georgia Inst. of Technol., Atlanta, GA (Perdisci, R.; Dagon, D.; Wenke Lee; Fogla, P.; Sharif, M.) |
| Abstract | Several syntactic-based automatic worm signature generators, e.g., Polygraph, have recently been proposed. These systems typically assume that a set of suspicious flows are provided by a flow classifier, e.g., a honeynet or an intrusion detection system, that often introduces "noise" due to difficulties and imprecision inflow classification. The algorithms for extracting the worm signatures from the flow data are designed to cope with the noise. It has been reported that these systems can handle a fairly high noise level, e.g., 80% for Polygraph. In this paper, we show that if noise is introduced deliberately to mislead a worm signature generator, a much lower noise level, e.g., 50%, can already prevent the system from reliably generating useful worm signatures. Using Polygraph as a case study, we describe a new and general class of attacks whereby a worm can combine polymorphism and misleading behavior to intentionally pollute the dataset of suspicious flows during its propagation and successfully mislead the automatic signature generation process. This study suggests that unless an accurate and robust flow classification process is in place, automatic syntactic-based signature generators are vulnerable to such noise injection attacks |
| Sponsorship | IBM Corp |
| Starting Page | 15 |
| Ending Page | 31 |
| File Size | 423351 |
| Page Count | 17 |
| File Format | |
| ISBN | 0769525741 |
| ISSN | 10816011 |
| DOI | 10.1109/SP.2006.26 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-05-21 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Noise generators Intrusion detection Noise level Algorithm design and analysis Protection Classification algorithms Data mining Pollution Noise robustness Manuals |
| Content Type | Text |
| Resource Type | Article |
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