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Boosting the Scalability of Botnet Detection Using Adaptive Traffic Sampling
Proceedings of the 6th ACM Symposium on Information, Computer and Communications Security
  • Junjie Zhang, Wright State University - Main Campus
  • Xiapu Luo
  • Roberto Perdisci
  • Guofei Gu
  • Wenke Lee
  • Nick Feamster
Document Type
Conference Proceeding
Publication Date
3-1-2011
Disciplines
Abstract
Botnets pose a serious threat to the health of the Internet. Most current network-based botnet detection systems require deep packet inspection (DPI) to detect bots. Because DPI is a computational costly process, such detection systems cannot handle large volumes of traffic typical of large enterprise and ISP networks. In this paper we propose a system that aims to efficiently and effectively identify a small number of suspicious hosts that are likely bots. Their traffic can then be forwarded to DPI-based botnet detection systems for fine-grained inspection and accurate botnet detection. By using a novel adaptive packet sampling algorithm and a scalable spatial-temporal flow correlation approach, our system is able to substantially reduce the volume of network traffic that goes through DPI, thereby boosting the scalability of existing botnet detection systems. We implemented a proof-of-concept version of our system, and evaluated it using real-world legitimate and botnet-related network traces. Our experimental results are very promising and suggest that our approach can enable the deployment of botnet-detection systems in large, high-speed networks.
Comments

Presented at the 6th ACM Symposium on Information, Computer and Communications Security, Hong Kong, China.

DOI
10.1145/1966913.1966930
Citation Information
Junjie Zhang, Xiapu Luo, Roberto Perdisci, Guofei Gu, et al.. "Boosting the Scalability of Botnet Detection Using Adaptive Traffic Sampling" Proceedings of the 6th ACM Symposium on Information, Computer and Communications Security (2011) p. 124 - 134 ISSN: 978-1-4503-0564-8
Available at: http://works.bepress.com/junjie_zhang/4/