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The Forensic Validity of Visual Analytics

机译:视觉分析的法证效力

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The wider use of visualization and visual analytics in wide ranging fields has led to the need for visual analytics capabilities to be legally admissible, especially when applied to digital forensics. This brings the need to consider legal implications when performing visual analytics, an issue not traditionally examined in visualization and visual analytics techniques and research. While digital data is generally admissible under the Federal Rules of Evidence [ 10] [21 ], a comprehensive validation of the digital evidence is considered prudent. A comprehensive validation requires validation of the digital data under rules for authentication, hearsay, best evidence rule, and privilege.Additional issues with digital data arise when exploring digital data related to admissibility and the validity of what information was examined, to what extent, and whether the analysis process was sufficiently covered by a search warrant. For instance, a search warrant generally covers very narrow requirements as to what law enforcement is allowed to examine and acquire during an investigation. When searching a hard drive for child pornography, how admissible is evidence of an unrelated crime, i.e. drug dealing. This is further complicated by the concept of "in plain view". When performing an analysis of a hard drive what would be considered "in plain view" when analyzing a hard drive. The purpose of this paper is to discuss the issues of digital forensics and the related issues as they apply to visual analytics and identify how visual analytics techniques fit into the digital forensics analysis process, how visual analytics techniques can improve the legal admissibility of digital data, and identify what research is needed to further improve this process. The goal of this paper is to open up consideration of legal ramifications among the visualization community; the author is not a lawyer and the discussions are not meant to be inclusive of all differences in laws between states and countries.
机译:可视化和可视化分析在广泛领域中的广泛使用导致对可视化分析功能的合法要求,尤其是在应用于数字取证时。这就带来了在执行视觉分析时要考虑法律隐含的问题,而在可视化和视觉分析技术及研究中传统上并未对此问题进行研究。虽然根据联邦证据规则[10] [21]通常可以接受数字数据,但对数字证据的全面验证被认为是审慎的。全面的验证需要根据身份验证,传闻证据,最佳证据规则和特权规则对数字数据进行验证。在探索与可接受性以及所检查的信息的有效性和范围有关的数字数据时,数字数据还会出现其他问题。搜查令是否充分涵盖了分析过程。例如,搜查令通常涵盖关于在调查过程中允许执法人员检查和获取何种执法的非常狭窄的要求。当在硬盘上搜索儿童色情制品时,与犯罪无关的证据(例如毒品交易)的可接受性如何。 “纯视图”的概念使这一点更加复杂。在对硬盘驱动器进行分析时,在分析硬盘驱动器时会被视为“普通视图”。本文的目的是讨论数字取证的问题以及它们应用于视觉分析的相关问题,并确定视觉分析技术如何适合数字取证分析过程,视觉分析技术如何改善数字数据的法律可接纳性,并确定需要进行哪些研究以进一步改善此过程。本文的目的是在可视化社区中开放对法律后果的考虑。作者不是律师,讨论内容并不包含州与国家之间法律上的所有差异。

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