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Privacy risk assessment and users' awareness for mobile apps permissions

机译:隐私风险评估和用户对移动应用程序权限的了解

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Mobile applications have access to users' data. This raises a potential privacy concern since users' personal information is collected and revealed to third parties without their consent. In this paper we propose a proactive user-oriented approach towards users' awareness of the privacy risk involved with granting permissions to Android applications. We present a dynamic privacy scoring model that assesses the risk to users' privacy associated to an application which requires a set of permissions. The parameters of this model are the severity and the relative importance of permissions and their interactions. Severity is evaluated according to a standard severity assessment method. The relative importance is estimated according to an analytic method. An experimental study on a set of 64 applications has been conducted. Association rules between permissions have been identified by using a data mining algorithm.
机译:移动应用程序可以访问用户的数据。由于用户的个人信息未经他们的同意收集并透露给第三方,因此这引起了潜在的隐私问题。在本文中,我们提出了一种主动的面向用户的方法,以使用户意识到与向Android应用程序授予权限有关的隐私风险。我们提出了一个动态的隐私评分模型,该模型评估与需要一组权限的应用程序相关的用户隐私风险。该模型的参数是权限及其交互的严重性和相对重要性。严重性根据标准严重性评估方法进行评估。相对重要性根据一种分析方法进行估算。已经对一组64个应用程序进行了实验研究。权限之间的关联规则已通过使用数据挖掘算法进行了标识。

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