Determining the Effectiveness of Data Remanence Prevention in the AWS Cloud

B. Snyder, James H. Jones
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引用次数: 1

Abstract

Previous efforts to detect cross-instance cloud remanence have consisted of searching current instance unallocated space for fragments easily attributable to a prior user or instance, and results were necessarily dependent on the specific instances tested and the search terms employed by the investigator. In contrast, this work developed, tested, and applied a general method to detect potential cross-instance cloud remanence that does not depend on specific instances or search terms. This method collects unallocated space from multiple cloud virtual machine instances based on the same cloud provider template. Empty sectors and sectors which also appear in the allocated space of that instance are removed from the candidate remanence list, and the remaining sectors are compared to sectors from instances based on other templates from that same provider; a matching sector indicate potential cross-instance remanence. Matching sectors are further evaluated by considering contiguous sectors and mapping back to the source file from the other instance template, providing additional evidence that the recovered fragments may in fact be content from another instance. This work first found that unallocated space from multiple cloud instances based on the same template is not empty, random, nor identical - in itself an indicator of possible cross-instance remanence. This work also found sectors in unallocated space of multiple instances that matched contiguous portions of files from instances created from other templates, providing a focused area for determining whether cross-instance data remanence exists. This work contributes a general method to indicate potential cross-instance cloud data remanence which is not dependent on a specific provider or infrastructure, instance details, or the presence of specific user-attributable remnant fragments. A tool to implement the method was developed, validated, and then run on Amazon's AWS cloud service.
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确定AWS云中数据残留防护的有效性
以前检测跨实例云残留的努力包括搜索当前实例未分配的空间,以查找容易归因于先前用户或实例的片段,并且结果必然依赖于被测试的特定实例和调查者使用的搜索条件。相比之下,这项工作开发、测试并应用了一种通用方法来检测潜在的跨实例云残留,这种方法不依赖于特定的实例或搜索词。此方法基于相同的云提供商模板从多个云虚拟机实例收集未分配的空间。空扇区和也出现在该实例的已分配空间中的扇区将从候选剩余列表中删除,剩余的扇区将与基于同一提供者的其他模板的实例中的扇区进行比较;匹配扇区表示潜在的跨实例残留。通过考虑相邻扇区并从其他实例模板映射回源文件,进一步评估匹配扇区,从而提供额外的证据,证明恢复的片段实际上可能是来自另一个实例的内容。这项工作首先发现,基于相同模板的多个云实例的未分配空间不是空的、随机的,也不是相同的——这本身就是一个可能的跨实例剩余的指标。这项工作还在多个实例的未分配空间中发现了扇区,这些扇区与从其他模板创建的实例的文件的连续部分相匹配,为确定是否存在跨实例数据残留提供了一个重点区域。这项工作提供了一种通用的方法来指示潜在的跨实例云数据残留,这种残留不依赖于特定的提供商或基础设施、实例细节或特定用户可归属的残留碎片的存在。开发、验证了实现该方法的工具,然后在亚马逊的AWS云服务上运行。
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