Research Article
BotGAD: Detecting Botnets by Capturing Group Activities in Network Traffic
@INPROCEEDINGS{10.1145/1621890.1621893, author={Hyunsang Choi and Heejo Lee and Hyogon Kim}, title={BotGAD: Detecting Botnets by Capturing Group Activities in Network Traffic}, proceedings={4th International ICST Conference on Communication System Software and Middleware}, publisher={ACM}, proceedings_a={COMSWARE}, year={2010}, month={5}, keywords={}, doi={10.1145/1621890.1621893} }- Hyunsang Choi
Heejo Lee
Hyogon Kim
Year: 2010
BotGAD: Detecting Botnets by Capturing Group Activities in Network Traffic
COMSWARE
ACM
DOI: 10.1145/1621890.1621893
Abstract
Recent malicious attempts are intended to obtain financial benefits using a botnet which has become one of the major Internet security problems. Botnets can cause severe Internet threats such as DDoS attacks, identity theft, spamming, click fraud. In this paper, we define a group activity as an inherent property of the botnet. Based on the group activity model and metric, we develop a botnet detection mechanism, called BotGAD (Botnet Group Activity Detector). BotGAD enables to detect unknown botnets from large scale networks in real-time. Botnets frequently use DNS to rally infected hosts, launch attacks and update their codes. We implemented Bot- GAD using DNS traffic and showed the effectiveness by experiments on real-life network traces. BotGAD captured 20 unknown and 10 known botnets from two day campus network traces.
