Many Android applications collect data from users. When they do, they must protect this collected data according to the current legal frameworks. Such data protection has become even more important since the European Union rolled out the General Data Protection Regulation (GDPR). App developers have limited tool support to reason about data protection throughout their app development process. Although many Android applications state a privacy policy, privacy policy compliance checks are currently manual, expensive, and prone to error. One of the major challenges in privacy audits is the significant gap between legal privacy statements (in English text) and technical measures that Android apps use to protect their user's privacy. In this thesis, we will explore to what extent we can use static analysis to answer important questions regarding data protection. Our main goal is to design a tool based approach that aids app developers and auditors in ensuring data protection in Android applications, based on automated static program analysis.
翻译:许多安卓应用程序从用户那里收集数据。当它们这样做时,必须根据当前的法律框架保护这些收集的数据。自欧盟推出《通用数据保护条例》(GDPR)以来,这种数据保护变得更加重要。应用程序开发人员在整个应用程序开发过程中推理数据保护时有限的工具支持。尽管许多安卓应用程序说明了隐私政策,但隐私政策合规性检查目前是手动的、昂贵的且容易出错的。隐私审计中的一个主要挑战是法律隐私声明(英文文本)和安卓应用程序用于保护用户隐私的技术措施之间的显著差距。在本文中,我们将探讨在多大程度上可以使用静态分析回答有关数据保护的重要问题。我们的主要目标是设计一种基于静态程序分析的工具方法,以帮助应用程序开发人员和审计员确保安卓应用程序中的数据保护。