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Personal Information Disclosure of User-Profiles on Facebook

机译:个人信息披露Facebook上的用户配置文件

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摘要

Facebook, the most popular and largest Online Social Network (OSN) is a virtual community where people interact and connect with each other by creating a profile and share opinions and interests in different ways. In recent years, we have witnessed a massive participation of people in these communities which has resulted in the generation and availability of large volumes of personal and sensitive data in the public domain. Public disclosure of this information has exaggerated worries about the loss of privacy. In this work, we study the exposure and pattern of information disclosure of user-profiles on Facebook to understand how secure and private the personal profile information is. To do so, we extracted the public profile information of 134K Facebook users and examined the same in terms of disclosure of information and privacy loss. Most of the personal information is permissive by default to external entities by Facebook. Although a user has the provision of customizing privacy controls to make the information restricted to his neighborhood. Our findings depict that most of the users have remained unaware of these privacy controls as we see a large volume of profile information is in the public domain. We conducted a statistical analysis of the user profile data to understand the type of information disclosed by most of the users. We also carried out a gender-wise and age-distribution analysis on the extracted data. Furthermore, we have also discussed an alternative approach to Facebook’s Graph Application Programming Interface (API) for obtaining profile data
机译:Facebook,最受欢迎和最大的在线社交网络(OSN)是一个虚拟社区,人们通过以不同方式创建配置文件并分享意见和利益来互相交互和连接。近年来,我们目睹了这些社区中的人们大规模参与,这导致了公共领域的大量个人和敏感数据的发电和可用性。公开披露这些信息夸大了对丧失隐私的担忧。在这项工作中,我们研究Facebook上的用户配置文件信息披露的曝光和模式,以了解个人资料信息的安全和私人。为此,我们提取了134K Facebook用户的公开资料信息,并在披露信息和隐私损失方面进行了审查。大多数个人信息默认到Facebook的外部实体是允许的。虽然用户提供了提供自定义隐私控制,但要使信息限制在他的社区。我们的调查结果描绘了大多数用户仍然没有意识到这些隐私控制,因为我们看到大量的个人资料在公共领域。我们对用户简档数据进行了统计分析,以了解大多数用户所公开的信息类型。我们还对提取的数据进行了性别明智和年龄分布分析。此外,我们还讨论了Facebook的图形应用程序编程接口(API)的替代方法,以获取配置文件数据

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