SeePrivacy: Automated Contextual Privacy Policy Generation for Mobile Applications

• URL: http://arxiv.org/abs/2307.01691v3
• Date: Sun, 9 Jul 2023 15:54:08 GMT
• Title: SeePrivacy: Automated Contextual Privacy Policy Generation for Mobile Applications
• Authors: Shidong Pan, Zhen Tao, Thong Hoang, Dawen Zhang, Zhenchang Xing, Xiwei Xu, Mark Staples, and David Lo
• Abstract summary: SeePrivacy is designed to automatically generate contextual privacy policies for mobile apps. Our method synergistically combines mobile GUI understanding and privacy policy document analysis. 96% of the retrieved policy segments can be correctly matched with their contexts.
• Score: 21.186902172367173
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Privacy policies have become the most critical approach to safeguarding individuals' privacy and digital security. To enhance their presentation and readability, researchers propose the concept of contextual privacy policies (CPPs), aiming to fragment policies into shorter snippets and display them only in corresponding contexts. In this paper, we propose a novel multi-modal framework, namely SeePrivacy, designed to automatically generate contextual privacy policies for mobile apps. Our method synergistically combines mobile GUI understanding and privacy policy document analysis, yielding an impressive overall 83.6% coverage rate for privacy-related context detection and an accuracy of 0.92 in extracting corresponding policy segments. Remarkably, 96% of the retrieved policy segments can be correctly matched with their contexts. The user study shows SeePrivacy demonstrates excellent functionality and usability (4.5/5). Specifically, participants exhibit a greater willingness to read CPPs (4.1/5) compared to original privacy policies (2/5). Our solution effectively assists users in comprehending privacy notices, and this research establishes a solid foundation for further advancements and exploration.

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