A Visual Analytics Approach to Detecting Server Redirections and Data Exfiltration

被引:0
|
作者
Wang, Weijie [1 ]
Yang, Baijian [1 ]
Chen, Victor Yingjie [2 ]
机构
[1] Purdue Univ, Dept Comp & Informat Technol, W Lafayette, IN 47906 USA
[2] Purdue Univ, Dept Comp Graph Technol, W Lafayette, IN 47906 USA
关键词
visual analytics; netflow; anomaly; server redirection; data exfiltration;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
How to better find potential cyberattacks is a challenging question for security researchers and practitioners. In recent years, visualization has been applied in the field of analyzing cybersecurity issues, but most work has not been able to provide better than non-visualization based techniques. In this paper, we innovatively designed a visual analytics system to allow analysts to overview network traffic and identify such suspicious such activities as server redirection attack and data exfiltration. Because of the nature of the problem, the overview design must be scalable, accurate, and fast. Through aggregating traffic data along the two dimensions of duration and payload, the system reveals key network traffic characteristics for the analyst to identify security events. The system is evaluated with the test data sets from VAST 2013 mini-challenge 3. The results are very encouraging and shed a more positive light on applying visual analytics in information security.
引用
收藏
页码:13 / 18
页数:6
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