Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 255

The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.

A Taxonomy of Botnet Structures

Dagon, David, Gu, Guofei, Lee, Christopher P., Lee, Wenke·2007·Twenty-Third Annual Computer Security Applications Conference (ACSAC 2007)

Abstract

We propose a taxonomy of botnet structures, based on their utility to the botmaster. We propose key metrics to measure their utility for various activities (e.g., spam, ddos). Using these performance metrics, we consider the ability of different response techniques to degrade or disrupt botnets. In particular, our models show that targeted responses are particularly effective against scale free botnets and efforts to increase the robustness of scale free networks comes at a cost of diminished transitivity. Botmasters do not appear to have any structural solutions to this problem in scale free networks. We also show that random graph botnets (e.g., those using P2P formations) are highly resistant to both random and targeted responses. We evaluate the impact of responses on different topologies using simulation and demonstrate the utility of our proposed metrics by performing novel measurements of a P2P network. Our analysis shows how botnets may be classified according to structure and given rank or priority using our proposed metrics. This may help direct responses and suggests which general remediation strategies are more likely to succeed.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1109/acsac.2007.44

Cites

40 of 40 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 40 references

Cited by

See all 255

Metadata

Authors
Dagon, D., Gu, G., Lee, C. P., & Lee, W.
Venue
Twenty-Third Annual Computer Security Applications Conference (ACSAC 2007)
Publisher
IEEE
Published
2007-12
Pages
325-339
OpenAlex
W2152955531
Cited by
255
References
40
FWCI
33.42
Type
conference paper
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: A Taxonomy of Botnet Structures. https://app.cochat.ai/papers/10.1109/acsac.2007.44
The paper
Dagon, D., Gu, G., Lee, C. P., & Lee, W. (2007). A Taxonomy of Botnet Structures. Twenty-Third Annual Computer Security Applications Conference (ACSAC 2007). https://doi.org/10.1109/acsac.2007.44

Data sources

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.