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Practical Attack Graph Generation for Network Defense
Abstract
Attack graphs are a valuable tool to network defenders, illustrating paths an attacker can use to gain access to a targeted network. Defenders can then focus their efforts on patching the vulnerabilities and configuration errors that allow the attackers the greatest amount of access. We have created a new type of attack graph, the multiple-prerequisite graph, that scales nearly linearly as the size of a typical network increases. We have built a prototype system using this graph type. The prototype uses readily available source data to automatically compute network reachability, classify vulnerabilities, build the graph, and recommend actions to improve network security. We have tested the prototype on an operational network with over 250 hosts, where it helped to discover a previously unknown configuration error. It has processed complex simulated networks with over 50,000 hosts in under four minutes
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Cited by
Model-based Security Metrics Using ADversary VIew Security Evaluation (ADVISE)
LeMay, E., Ford, M. D., Keefe, K., Sanders, W. H., & Muehrcke, C. (2011) · 2011 Eighth International Conference on Quantitative Evaluation of SysTems · doi:10.1109/qest.2011.34 · Cited by 128
Metadata
- Authors
- Ingols, K., Lippmann, R., & Piwowarski, K.
- Venue
- 2006 22nd Annual Computer Security Applications Conference (ACSAC'06)
- Publisher
- IEEE
- Published
- 2006-12
- Pages
- 121-130
- ISSN
- 1063-9527 (ISSN-L)
- OpenAlex
- W2100033648
- Cited by
- 379
- References
- 0
- FWCI
- 14.11
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Practical Attack Graph Generation for Network Defense. https://app.cochat.ai/papers/10.1109/acsac.2006.39
- The paper
- Ingols, K., Lippmann, R., & Piwowarski, K. (2006). Practical Attack Graph Generation for Network Defense. 2006 22nd Annual Computer Security Applications Conference (ACSAC'06). https://doi.org/10.1109/acsac.2006.39
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
