基于下载行为的前10名恶意软件/机器人聚类

Chaxiong Yukonhiatou, S. Kittitornkun, Hiroaki Kikuchi, Khamphao Sisaat, M. Terada, H. Ishii
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引用次数: 3

摘要

恶意软件可以通过特别的下载机制在互联网上传播到受害计算机。本研究试图基于2010年和2011年CCC (Cyber Clean Center)数据集对恶意软件/机器人下载前10名恶意软件的行为进行聚类。这些数据集包含了从日本几个独立的蜜罐收集的超过100万的下载日志,以观察恶意软件/机器人的流量和活动。尽管2010年的日和时模式非常相似,但2011年的情况却大不相同。因此,所提出的积分相关系数可以分别聚类2010年和2011年排名前10的恶意软件/机器人的3组和4组。
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Clustering Top-10 malware/bots based on download behavior
Malware can be spread over the Internet via especially download mechanism to the victim computers. This work tries to cluster malware/bots download behavior of Top-10 malware based on 2010 and 2011 CCC (Cyber Clean Center) datasets. The datasets contain more than one million download logs collected from several independent honeypots in Japan to observe malware/bot traffic and activities. Although the daily and hourly patterns are quite similar in 2010, those of 2011 are quite different. As a result, the proposed Integral Correlation Coefficient can cluster 3 and 4 groups of Top-10 malware/bots in 2010 and 2011, respectively.
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