Data Mining in Long-Term Honeypot Data

被引:7
作者
Fraunholz, Daniel [1 ]
Zimmermann, Marc [1 ]
Hafner, Alexander [1 ]
Schotten, Hans D. [1 ]
机构
[1] German Res Ctr Artificial Intelligence, Intelligent Networks Res Grp, D-67663 Kaiserslautern, Germany
来源
2017 17TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW 2017) | 2017年
关键词
FRAMEWORK;
D O I
10.1109/ICDMW.2017.92
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Criminal activity in the Internet is becoming more sophisticated. Traditional information security techniques hardly cope with recent trends. Honeypots proved to be a valuable source of threat intelligence. In this work several Honeypots are combined into a Honeynet and observed exploitation attempts. The Honeynet consists of six Honeypots and was operated for 222 days. 12 million exploitation attempts were captured. The captured data is examined and evaluated. Several hypotheses are proposed and analyzed. Dependencies and distribution within the data are identified and quantified. Investigated features are: Temporal and spatial distribution, attacked protocols, involved autonomous systems and the employed dictionaries.
引用
收藏
页码:649 / 656
页数:8
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