Lengthy and legally phrased privacy policies impede users' understanding of how mobile applications collect and process personal data. Prior work proposed Contextual Privacy Policies (CPPs) for mobile apps to display shorter policy snippets only in the corresponding user interface contexts, but the pipeline could not be deployable in real-world mobile environments. In this paper, we present PrivScan, the first deployable CPP Software Development Kit (SDK) for Android. It captures live app screenshots to identify GUI elements associated with types of personal data and displays CPPs in a concise, user-facing format. We provide a lightweight floating button that offers low-friction, on-demand control. The architecture leverages remote deployment to decouple the multimodal backend pipeline from a mobile client comprising five modular components, thereby reducing on-device resource demands and easing cross-platform portability. A feasibility-oriented evaluation shows an average execution time of 9.15\,s, demonstrating the practicality of our approach. The source code of PrivScan is available at https://github.com/buyanghc/PrivScan and the demo video can be found at https://www.youtube.com/watch?v=ck-25otfyHc.

翻译：冗长且法律术语化的隐私政策阻碍了用户理解移动应用程序如何收集和处理个人数据。先前的研究提出了针对移动应用的情境隐私策略（CPPs），仅在相应的用户界面情境中显示较短的策略片段，但该流程无法在实际移动环境中部署。本文提出了PrivScan，这是首个适用于Android的可部署CPP软件开发工具包（SDK）。它通过捕获实时应用截图来识别与各类个人数据相关的图形用户界面元素，并以简洁、面向用户的格式展示CPPs。我们提供了一个轻量级的悬浮按钮，支持低摩擦、按需控制。该架构利用远程部署，将多模态后端流程与包含五个模块化组件的移动客户端解耦，从而降低设备端资源需求并提升跨平台可移植性。一项以可行性为导向的评估显示平均执行时间为9.15秒，证明了我们方法的实用性。PrivScan的源代码可在https://github.com/buyanghc/PrivScan获取，演示视频可在https://www.youtube.com/watch?v=ck-25otfyHc观看。