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A Taxonomy of Botnet Structures

David Dagon, Guofei Gu, Christopher P. Lee, Wenke Lee

Open publisher page 256 citations

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.

About this research paper

What this paper is about

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.

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OpenAlex reports 256 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available 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.

Key concepts: Botnet, Computer science, Robustness (evolution), Network topology, Transitive relation, Denial-of-service attack, Computer security, Computer network

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