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|Title: ||Fast-Flux Bot Detection in Real Time|
|Authors: ||Ching-Hsiang Hsu;Chun-Ying Huang;Kuan-Ta Chen|
|Contributors: ||NTOU:Department of Computer Science and Engineering|
|Keywords: ||Botnet;Request delegation;Document fetch delay;Processing delay;Internet measurement;Supervised classification|
|Issue Date: ||2011-10-21T02:34:31Z
|Publisher: ||Proceedings of International Symposium on Recent Advances in Intrusion Detection (RAID-2010)|
|Abstract: ||Abstract:The fast-flux service network architecture has been widely adopted by bot herders to increase the productivity and extend the lifespan of botnets' domain names. A fast-flux botnet is unique in that each of its domain names is normally mapped to different sets of IP addresses over time and legitimate users' requests are handled by machines other than those contacted by users directly. Most existing methods for detecting fast-flux botnets rely on the former property. This approach is effective, but it requires a certain period of time, maybe a few days, before a conclusion can be drawn.
In this paper, we propose a novel way to detect whether a web service is hosted by a fast-flux botnet in real time. The scheme is unique because it relies on certain intrinsic and invariant characteristics of fast-flux botnets, namely, 1) the request delegation model, 2) bots are not dedicated to malicious services, and 3) the hardware used by bots is normally inferior to that of dedicated servers. Our empirical evaluation results show that, using a passive measurement approach, the proposed scheme can detect fast-flux bots in a few seconds with more than 96% accuracy, while the false positive/negative rates are both lower than 5%.
|Appears in Collections:||[資訊工程學系] 期刊論文|
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