EFFORT: A new host-network cooperated framework for efficient and effective bot malware detection

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Bots are still a serious threat to Internet security. Although a lot of approaches have been proposed to detect bots at host or network level, they still have shortcomings. Host-level approaches can detect bots with high accuracy. However they usually pose too much overhead on the host. While network-level approaches can detect bots with less overhead, they have problems in detecting bots with encrypted, evasive communication CC channels. In this paper, we propose EFFORT, a new host-network cooperated detection framework attempting to overcome shortcomings of both approaches while still keeping both advantages, i.e., effectiveness and efficiency. Based on intrinsic characteristics of bots, we propose a multi-module approach to correlate information from different host- and network-level aspects and design a multi-layered architecture to efficiently coordinate modules to perform heavy monitoring only when necessary. We have implemented our proposed system and evaluated on real-world benign and malicious programs running on several diverse real-life office and home machines for several days. The final results show that our system can detect all 17 real-world bots (e.g., Waledac, Storm) with low false positives (0.68%) and with minimal overhead. We believe EFFORT raises a higher bar and this host-network cooperated design represents a timely effort and a right direction in the malware battle.
Publisher
ELSEVIER SCIENCE BV
Issue Date
2013-09
Language
English
Article Type
Article
Citation

COMPUTER NETWORKS, v.57, no.13, pp.2628 - 2642

ISSN
1389-1286
DOI
10.1016/j.comnet.2013.05.010
URI
http://hdl.handle.net/10203/205460
Appears in Collection
EE-Journal Papers(저널논문)
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