Eventpad:使用可视化分析的快速恶意软件分析和逆向工程

B. Cappers, Paulus N. Meessen, S. Etalle, J. V. Wijk
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引用次数: 26

摘要

对网络环境中的恶意软件活动进行取证分析是必要的,但在事件响应中非常昂贵且耗时。在一个非常劳动密集型的过程中,需要筛选大量的数据,寻找表明恶意软件在公司网络中如何表现的迹象。我们相信数据简化和可视化技术可以帮助安全分析师研究网络流量样本中的行为模式(例如,PCAP)。我们认为,在这种流量模式的发现可以帮助我们快速了解入侵行为,如恶意软件活动如何展开,并与其他流量区分开来。在本文中,我们介绍了一个可视化分析工具EventPad的案例研究,并说明了如何使用它来快速洞察使用规则,聚合和选择的PCAP流量分析。我们展示了该工具在涉及办公室流量和勒索软件活动的真实数据集上的有效性。
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Eventpad: Rapid Malware Analysis and Reverse Engineering using Visual Analytics
Forensic analysis of malware activity in network environments is a necessary yet very costly and time consuming part of incident response. Vast amounts of data need to be screened, in a very labor-intensive process, looking for signs indicating how the malware at hand behaves inside e.g., a corporate network. We believe that data reduction and visualization techniques can assist security analysts in studying behavioral patterns in network traffic samples (e.g., PCAP). We argue that the discovery of patterns in this traffic can help us to quickly understand how intrusive behavior such as malware activity unfolds and distinguishes itself from the rest of the traffic.In this paper we present a case study of the visual analytics tool EventPad and illustrate how it is used to gain quick insights in the analysis of PCAP traffic using rules, aggregations, and selections. We show the effectiveness of the tool on real-world data sets involving office traffic and ransomware activity.
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