Online Social Network Information Forensics: A Survey on Use of Various Tools and Determining How Cautious Facebook Users are?

Amber Umair, P. Nanda, Xiangjian He
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引用次数: 12

Abstract

Online Social Networks (OSN) such as Facebook, Twitter, LinkedIn, and Instagram are heavily used to socialize, entertain or gain insights on people behavior and their activities. Everyday terabytes of data is generated over these networks, which is then used by the businesses to generate revenue or misused by the wrongdoers to exploit vulnerabilities of these social network platforms. Specifically social network information helps in extracting various important features such as; user association, access pattern, location information etc. Recent research shows, many such features could be used to develop novel attack models and investigate further into defending the users from exposing their information to outsiders. This paper analyzes some of the available tools to extract OSN information and discusses research work on similar type of unstructured data. Recent research works, which focus on gathering bits and pieces of information to extract meaningful results for digital forensics, has been discussed. An online survey is conducted to gauge the cautiousness of users in social media usage in terms of personal information dissemination.
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在线社交网络信息取证:对各种工具使用的调查和确定Facebook用户的谨慎程度?
在线社交网络(OSN),如Facebook、Twitter、LinkedIn和Instagram,被大量用于社交、娱乐或了解人们的行为和活动。这些网络每天都会产生数兆字节的数据,然后这些数据被企业用来创收,或者被不法分子滥用来利用这些社交网络平台的漏洞。具体来说,社交网络信息有助于提取各种重要特征,例如;用户关联、访问模式、位置信息等。最近的研究表明,许多这样的特征可以用来开发新的攻击模型,并进一步研究如何保护用户不向外界暴露他们的信息。本文分析了一些可用的OSN信息提取工具,并讨论了类似类型的非结构化数据的研究工作。讨论了最近的研究工作,重点是收集零碎的信息,以提取有意义的数字取证结果。我们进行了一项在线调查,以衡量用户在社交媒体使用中对个人信息传播的谨慎程度。
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