基于ReFS $Logfile中删除模式的数据擦除工具识别

IF 2 4区 医学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Forensic Science International-Digital Investigation Pub Date : 2023-10-01 DOI:10.1016/j.fsidi.2023.301607
Eun Ji Lee , Seo Yeon Lee , Hyeon Kwon , Sung Jin Lee , Gi Bum Kim
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引用次数: 0

摘要

数据擦除工具通过重复覆盖数字设备上的数据永久删除文件,使文件恢复不可能。与传统的删除方法(仅删除指向数据的文件系统指针)不同,这些工具被设计为完全且不可挽回地擦除数据。这种方法可以用来抹杀犯罪证据。鉴于此类工具的日益流行,对永久删除行为的全面分析是必不可少的,特别是关于弹性文件系统(ReFS)。在本研究中,我们提出了一种检测ReFS 3.7中有关数据擦除工具和算法的用户行为的方法。我们的方法依赖于这样一个事实,即文件修改被记录在$Logfile的重做记录中,并且重做记录的操作码值取决于所使用的数据擦除工具。由于操作码只分析到3.4版本,所以我们分析了新更新的操作码。最初,我们选择了12种最常用的数据擦除工具进行研究。在模式分析阶段,我们应用每个工具支持的算法,为每个工具生成不同的删除模式。这是通过使用连续的操作码来制定模式并监视文件和目录名中的转换来实现的。在$Logfile中识别的模式允许我们确定部署了哪个数据擦除工具。所提出的方法不仅简化了数据擦除工具的识别,而且简化了所显示的特定删除行为的识别。我们开发了一种结合所提出方法的工具。我们随后的验证证实了我们的方法和工具在准确检测综合删除工具使用方面的有效性。这些发现为获取ReFS中用户删除行为的数字证据提供了宝贵的见解。我们提出的方法将有助于数字法医检测和识别数据擦除工具的行为。
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Identification of data wiping tools based on deletion patterns in ReFS $Logfile

Data wiping tools permanently delete files by repeatedly overwriting data on a digital device, making file recovery impossible. Unlike the conventional deletion methods, which merely remove the file system pointer to the data, these tools are designed to entirely and irretrievably erase the data. This method can be exploited to obliterate evidence of a crime. Given the growing prevalence of such tools, a comprehensive analysis of permanent deletion behavior is essential, especially concerning the Resilient File System (ReFS). In this study, we propose a method for detecting user behavior concerning data wiping tools and algorithms in ReFS 3.7. Our approach relies on the fact that file modifications are logged in the redo record of the $Logfile, and that the opcode value of the redo record varies depending on the data wiping tool used. Since opcodes were only analyzed up to version 3.4, we analyzed the newly updated opcodes. Initially, we selected the 12 most commonly used data wiping tools for our research. In the pattern analysis phase, we applied the algorithms supported by each tool, generating a distinct deletion pattern for each one. This was accomplished by utilizing consecutive opcodes to formulate the patterns and monitor transitions in file and directory names. The patterns discerned in the $Logfile allowed us to determine which data wiping tool was deployed. The proposed methodology simplifies the identification of not only which data wiping tool has been used, but also the specific deletion behavior exhibited. We developed a tool incorporating the proposed method. Our subsequent verification confirmed the effectiveness of our methodology and tools in accurately detecting the use of comprehensive deletion tools. These findings contribute valuable insights to the acquisition of digital evidence of user deletion behavior in ReFS. Our proposed methodology will help digital forensic examiners in the detection and identification of data wiping tools' behavior.

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来源期刊
CiteScore
5.90
自引率
15.00%
发文量
87
审稿时长
76 days
期刊最新文献
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