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A Visual Model for Privacy Awareness and Understanding in Online Social Networks

机译:在线社交网络中隐私意识和理解的可视模型

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The number of users participating in online social networks is increasing significantly recently. As a result, the amount of information created and shared by them is exploding. On one hand, sharing information online helps people stay in touch with each other, although virtually. But on the other hand, sharing too much information may lead to sensitive personal data being leaked unexpectedly. To protect their users' private information, online social network providers often employ technical methods like access control and cryptography among others. Although these approaches are good enough for their designated purposes, they provide little to no protection when are used wrongly. To reduce the number of mistakes users may make, online social network providers also offers them visual interfaces, instead of lengthy and boring texts, for privacy settings selection and configuration. Unfortunately, private information is stilled shared publicly, with or without its owners' awareness. In this paper, we attempt to mitigate the privacy leakage problem by proposing a novel visual model for measuring and representing users' privacy in online social network environment and associated privacy controller for protecting it. A concrete instance of the model has been designed and implemented. A demonstration of the model instance has been executed for one of the biggest social networks, Facebook. Initial results indicate the effectiveness of the proposed model and its concrete instance. However, a more important and difficult problem is whether online social network providers are willing to apply these results, which may affect sharing activities and go against their business objectives.
机译:最近,参与在线社交网络的用户数量显着增加。结果,它们创建和共享的信息量呈爆炸式增长。一方面,在线共享信息可以帮助人们保持联系,尽管实际上是这样。但另一方面,共享太多信息可能会导致敏感的个人数据意外泄漏。为了保护用户的私人信息,在线社交网络提供商经常采用诸如访问控制和加密之类的技术方法。尽管这些方法足以满足其指定的目的,但是如果使用不当,它们几乎不会提供任何保护。为了减少用户可能犯的错误,在线社交网络提供商还为他们提供了可视化界面,而不是冗长乏味的文本,用于隐私设置的选择和配置。不幸的是,无论有没有所有者的意识,私人信息仍然会公开共享。在本文中,我们试图通过提出一种新颖的视觉模型来度量和表示在线社交网络环境中用户的隐私,并通过相关的隐私控制器对其进行保护,以减轻隐私泄露问题。该模型的具体实例已经设计和实现。已针对最大的社交网络之一Facebook执行了该模型实例的演示。初步结果表明了该模型及其具体实例的有效性。但是,一个更为重要和困难的问题是在线社交网络提供商是否愿意应用这些结果,这可能会影响共享活动并违背其业务目标。

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