检测服务器重定向和数据泄露的可视化分析方法

Weijie Wang, B. Yang, Victor Y. Chen
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引用次数: 6

摘要

如何更好地发现潜在的网络攻击是安全研究人员和从业人员面临的一个具有挑战性的问题。近年来,可视化已被应用于网络安全问题分析领域,但大多数工作还不能提供比非可视化技术更好的结果。在本文中,我们创新地设计了一个可视化分析系统,允许分析人员概述网络流量并识别诸如服务器重定向攻击和数据泄露等可疑活动。由于问题的性质,概览设计必须是可伸缩的、准确的和快速的。系统通过对持续时间和有效载荷两个维度的流量数据进行聚合,揭示网络流量的关键特征,供分析人员识别安全事件。利用VAST 2013 mini-challenge 3的测试数据集对系统进行了评估。结果非常鼓舞人心,并为可视化分析在信息安全中的应用提供了更积极的启示。
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A visual analytics approach to detecting server redirections and data exfiltration
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.
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