AutoPPG:迈向Android应用程序隐私政策的自动生成

Le Yu, Zhang Tao, Xiapu Luo, Lei Xue
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引用次数: 53

摘要

隐私政策是一份声明,告知用户他们的信息将如何被收集、使用和披露。未能提供正确的隐私政策可能会导致罚款。然而,编写隐私策略是乏味且容易出错的,因为作者可能不太了解源代码,这些源代码可能是由其他人编写的(例如,外包),或者不知道没有源代码的第三方库的内部。在本文中,我们提出并开发了一个名为AutoPPG的新系统,用于自动构建正确且可读的描述,以促进Android应用程序(即应用程序)隐私策略的生成。对于一个应用程序,AutoPPG首先通过各种静态代码分析来描述其与用户隐私信息相关的行为,然后应用自然语言处理技术生成正确且可访问的句子来描述这些行为。基于真实应用和众包的实验结果表明:(1)AutoPPG创建了正确且易于理解的隐私政策描述;(2)与现有隐私政策相比,AutoPPG构建的隐私政策通常会披露更多与用户隐私信息相关的操作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AutoPPG: Towards Automatic Generation of Privacy Policy for Android Applications
A privacy policy is a statement informing users how their information will be collected, used, and disclosed. Failing to provide a correct privacy policy may result in a fine. However, writing privacy policy is tedious and error-prone, because the author may not well understand the source code, which could be written by others (e.g., outsourcing), or does not know the internals of third-party libraries without source codes. In this paper, we propose and develop a novel system named AutoPPG to automatically construct correct and readable descriptions to facilitate the generation of privacy policy for Android applications (i.e., apps). Given an app, AutoPPG first conducts various static code analyses to characterize its behaviors related to users' private information and then applies natural language processing techniques to generating correct and accessible sentences for describing these behaviors. The experimental results using real apps and crowdsourcing indicate that: (1) AutoPPG creates correct and easy-to-understand descriptions for privacy policies; and (2) the privacy policies constructed by AutoPPG usually reveal more operations related to users' private information than existing privacy policies.
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