PScore:在线社交网络中增强隐私意识的框架

Georgios Petkos, S. Papadopoulos, Y. Kompatsiaris
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引用次数: 30

摘要

近年来,社交媒体使用的惊人增长引发了许多与隐私有关的问题。在本文中,我们提出了一个框架,用于提高在线社交网络(OSN)用户对其披露的信息的认识,这些信息可以被OSN服务运营商以及可以访问其数据的第三方推断出来。该框架采用语义、分层评分结构的形式,使用户能够轻松浏览他们在社交网络中存在的与隐私相关的不同方面。与以前的隐私评分方法相反,所提出的框架提供了更精细、更直观的隐私信息组织。重要的是,它还考虑了用户共享内容中明确提到的信息,以及可能从中推断出的隐含信息。我们提供了该框架的开源实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PScore: A Framework for Enhancing Privacy Awareness in Online Social Networks
The phenomenal increase in the use of social media in recent years has raised a number of issues related to privacy. In this paper, we propose a framework for raising the awareness of Online Social Network (OSN) users with respect to the information about them that is disclosed and that can be inferred by OSN service operators as well as by third parties that can access their data. This framework takes the form of a semantic, hierarchical scoring structure, that enables users to easily browse over different privacy-related aspects of their presence in a social network. Contrary to previous privacy scoring approaches, the proposed framework provides a finer and more intuitive organization of privacy information. Importantly, it also takes into account both information that is explicitly mentioned in users' shared content, as well as implicit information, that may be inferred from it. We make available an open source implementation of the framework.
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