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A semi-automated forensic investigation model for online social networks

机译:用于在线社交网络的半自动法医调查模型

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摘要

Investigating the online social network profiles of victims, suspects, and witnesses are now part of almost every legal investigation, either it involves a criminal offense, financial fraud, or domestic lawsuit. However, investigating online social networks (OSN) is a technically complicated process that becomes more challenging due to the legal issues of privacy and authentication. Completely manual investigative methods are not feasible for OSN investigations due to the immense size and heterogeneity of social networks. However, the existing models for digital forensic investigation are not supporting automated or semi-automated forensic investigation processes. Furthermore, they are not addressing the fundamental differences and specific requirements of online social networks. The model presented in this work incorporates the robust features of standard investigation models and proposes a digital forensic investigation process model that explicitly addresses the necessities of OSN investigations. This work is addressing the issues of automating the forensic collection and analysis processes, defining crime scene boundaries, and outlining reasonable iterative collection procedures in online social network forensic investigation. This work is evaluated using a case study and is compared with existing practices and standards.
机译:调查受害者,嫌疑人和目击者的在线社交网络概况现在几乎所有法律调查的一部分,无论是涉及刑事犯罪,金融欺诈还是国内诉讼。然而,调查在线社交网络(OSN)是一种技术上复杂的过程,由于隐私和认证的法律问题,由于隐私和认证的法律问题而变得更具挑战性。由于社交网络的巨大规模和异质性,OSN调查完全是手动调查方法不可行。然而,现有的数字法医调查模型不支持自动化或半自动法医调查过程。此外,他们没有解决在线社交网络的基本差异和具体要求。本工作中提出的模型包括标准调查模型的强大特征,并提出了一种数字法医调查过程模型,明确地解决了OSN调查的必要性。这项工作正在解决自动化法医收集和分析过程,定义犯罪现场边界的问题,并概述在线社交网络法医调查中的合理迭代收集程序。使用案例研究评估此工作,并与现有的实践和标准进行比较。

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