MITC Viz:云中人威胁感知的可视化分析

Chiun-How Kao, Jyun-Han Dai, R. Ko, Yu-Ting Kuang, Chi-Ping Lai, Ching-Hao Mao
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引用次数: 4

摘要

一些常见的文件同步服务(如GoogleDrive, Dropbox等)被用作命令和控制(C&C)和数据泄露(MITC)攻击的基础设施。在不使用任何漏洞的情况下,普通安全措施不容易检测到MITC,并且重新配置这些服务很容易将它们变成攻击工具。在本研究中,我们提出了交互式可视化威胁资源管理器,可以直观地发现隐藏在数据中的潜在云威胁,最终显著提高分析效率。向下钻取和快速响应可视化分析为云管理员提供了云资源和用户行为之间的全面和深入的视图。此外,考虑用户社交行为和业务工作流行为的协同风险估计器提高了分析性能。通过学习个人用户过去的行为和社会网络的关系,积累行为模型,不断适应企业环境的变化。分析人员可以从异常的云资源访问中快速识别高风险访问行为的位置,并对异常模式和访问行为进行深入分析。为了说明这种方法的有效性,我们在两个真实世界的数据集上进行了示例探索,以检测和理解正在进行的潜在高级持续威胁。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MITC Viz: Visual Analytics for Man-in-the-Cloud Threats Awareness
Several common file synchronization services (such as GoogleDrive, Dropbox and so on) are employed as infrastructure for being used by command and control(C&C) and data exfiltration, saying Man-in-the-Cloud (MITC) attacks. MITC is not easily detected by common security measures result in without using any exploits, and re-configuration of these services can easily turn them into an attack tool. In this study, we propose Interactive Visualization Threats Explorer that can be with intuition to aware the potential cloud threats hiding in data and eventually improve the analyzing effectiveness significantly. Drill-down and quick response visualization analytics provides cloud administrators full and deep views between cloud resources and users behavior. In addition, Collaborative Risk Estimator which considers users social and business workflow behavior enhance analysis performance. By learning from past behavior of an individual user and social network relations, rolling up behavior models to continue adapt enterprise environment changes. Analyst can quickly aware high risk access behavior locality from abnormal cloud resource access and drill-down the unusual patterns and access behavior. To illustrate the effectiveness of this approach, we present example explorations on two real-world data sets for the detection and understanding of potential Advanced Persistent Threats in progress.
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