Presentation 2015-03-03
A detection system which uses DNS traffic features to detect domains which are related to botnets
Wataru TSUDA, Youki KADOBAYASHI, Takeshi OKUDA, Hiroaki HAZEYAMA,
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Abstract(in English) We face cyber attacks such as illegal money transfer via net-banking, spam mail and DDoS attacks caused by botnet. In this research, we propose a novel detection system called Domain Forest for detecting botnet-related domain names using traffic analysis. Domain Forest system aims to detect not only specific botnet, but also many variations of it. To accomplish this objective, we apply many kinds of features based on periodicity, similarity, simultaneity, rendundancy and locality from DNS response packet. We experimented with one month of real DNS traffic data, and our system achieved 99.24% detection rates and 0.53% false positive rates.
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Keyword(in English) malware / botnet / dns / machine learning
Paper # ICSS2014-63
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Conference Information
Committee ICSS
Conference Date 2015/2/24(1days)
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Paper Information
Registration To Information and Communication System Security (ICSS)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A detection system which uses DNS traffic features to detect domains which are related to botnets
Sub Title (in English)
Keyword(1) malware
Keyword(2) botnet
Keyword(3) dns
Keyword(4) machine learning
1st Author's Name Wataru TSUDA
1st Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology()
2nd Author's Name Youki KADOBAYASHI
2nd Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology
3rd Author's Name Takeshi OKUDA
3rd Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology
4th Author's Name Hiroaki HAZEYAMA
4th Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology
Date 2015-03-03
Paper # ICSS2014-63
Volume (vol) vol.114
Number (no) 489
Page pp.pp.-
#Pages 6
Date of Issue