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enList: Automatically Simplifying Privacy Policies

机译:入伍:自动简化隐私政策

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Online social networking sites have become extremely popular. Due to the pervasiveness of these sites, it is important to provide tools that allow users to specify detailed policies controlling access to their data. However, the policies specified using existing tools are often complex, verbose, and difficult to understand. In this paper, we study the policy simplification problem. Given a complex or verbose policy, our goal is to automatically produce an equivalent policy that is easier to understand. We propose a novel framework called enList, which automatically extracts friend "lists" (semantically meaningful subgroups of a user's friends) and then simplifies an existing policy using the lists. A laboratory-based user study confirms that the resulting policies are easier for users to comprehend, remember, and maintain than the policies produced by an existing recommendation tool.
机译:在线社交网站变得非常受欢迎。由于这些站点的普及性,提供了允许用户指定控制对其数据的详细策略的工具非常重要。但是,使用现有工具指定的策略通常很复杂,冗长,难以理解。在本文中,我们研究了策略简化问题。鉴于复杂或冗长的政策,我们的目标是自动生成更容易理解的等效政策。我们提出了一种名为“入伍”的新颖框架,它会自动提取朋友“列表”(语义上有意义的用户的朋友子组),然后使用列表简化现有策略。基于实验室的用户学习证实,由现有推荐工具产生的策略,用户可以更轻松地确认由此产生的策略更容易理解,记住和维护。

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