The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Vigilante: end-to-end containment of internet worms
Abstract
Worm containment must be automatic because worms can spread too fast for humans to respond. Recent work has proposed network-level techniques to automate worm containment; these techniques have limitations because there is no information about the vulnerabilities exploited by worms at the network level. We propose Vigilante, a new end-to-end approach to contain worms automatically that addresses these limitations. Vigilante relies on collaborative worm detection at end hosts, but does not require hosts to trust each other. Hosts run instrumented software to detect worms and broadcast self-certifying alerts (SCAs) upon worm detection. SCAs are proofs of vulnerability that can be inexpensively verified by any vulnerable host. When hosts receive an SCA, they generate filters that block infection by analysing the SCA-guided execution of the vulnerable software. We show that Vigilante can automatically contain fast-spreading worms that exploit unknown vulnerabilities without blocking innocuous traffic.
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Cites
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Hethcote, H. W. (2000) · SIAM Review · doi:10.1137/s0036144500371907 · Cited by 6,687
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Snort - Lightweight Intrusion Detection for Networks
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Cited by
de Moura, L., & Bjørner, N. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-78800-3_24 · Cited by 6,595
Enck (2014) · doi:10.1145/2619091 · Cited by 1,203
Carat: collaborative energy diagnosis for mobile devices
Oliner, A. J., Iyer, A. P., Stoica, I., Lagerspetz, E., & Tarkoma, S. (2013) · Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems · doi:10.1145/2517351.2517354 · Cited by 148
Metadata
- Authors
- Costa, M., Crowcroft, J., Castro, M., Rowstron, A., Zhou, L., Zhang, L., & Barham, P.
- Venue
- ACM SIGOPS Operating Systems Review
- Published
- 2005-10-20
- Volume
- 39
- Issue
- 5
- Pages
- 133-147
- ISSN
- 0163-5980 (ISSN-L)
- OpenAlex
- W2165100126
- Cited by
- 441
- References
- 33
- FWCI
- 70.99
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
