VPVet：审查虚拟现实应用隐私政策
VPVet: Vetting Privacy Policies of Virtual Reality Apps
AI总结：
本文提出VPVet系统，通过分析隐私政策的可用性、完整性、粒度、最小化和CUS一致性，自动审查VR应用隐私合规问题，并构建了包含11,923个VR应用的最大数据集VRPP，揭示了VR生态系统中严重的隐私问题。
摘要：
虚拟现实（VR）应用相比运行在个人电脑或智能手机上的网页/移动应用，能够收集更广泛的用户数据。现有法律和隐私法规强调，VR开发者应通过隐私政策告知用户哪些数据被收集/使用/共享（CUS）。然而，VR生态系统中的隐私政策仍处于早期阶段，许多开发者未能编写符合法规并满足用户期望的适当隐私政策。本文提出VPVet，用于自动审查VR应用的隐私政策合规问题。VPVet首先分析VR隐私政策的可用性和完整性，然后基于三个关键标准细化分析：CUS声明的粒度、最小化和一致性。我们的研究建立了首个且目前最大的VR隐私政策数据集VRPP，包含来自10个主流平台的11,923个不同VR应用的隐私政策。审查结果揭示了VR生态系统中严重的隐私问题，包括隐私政策可用性有限、质量差、粒度粗糙、缺乏对VR特性的适配，以及隐私政策中CUS声明与实际行为之间的不一致。我们将VPVet系统及研究发现开源在https://github.com/kalamoo/PPAudit，旨在提高VR社区的意识，并为该领域的进一步研究铺平道路。
英文摘要：
Virtual reality (VR) apps can harvest a wider range of user data than web/mobile apps running on personal computers or smartphones. Existing law and privacy regulations emphasize that VR developers should inform users of what data are collected/used/shared (CUS) through privacy policies. However, privacy policies in the VR ecosystem are still in their early stages, and many developers fail to write appropriate privacy policies that comply with regulations and meet user expectations. In this paper, we propose VPVet to automatically vet privacy policy compliance issues for VR apps. VPVet first analyzes the availability and completeness of a VR privacy policy and then refines its analysis based on three key criteria: granularity, minimization, and consistency of CUS statements. Our study establishes the first and currently largest VR privacy policy dataset named VRPP, consisting of privacy policies of 11,923 different VR apps from 10 mainstream platforms. Our vetting results reveal severe privacy issues within the VR ecosystem, including the limited availability and poor quality of privacy policies, along with their coarse granularity, lack of adaptation to VR traits and the inconsistency between CUS statements in privacy policies and their actual behaviors. We open-source VPVet system along with our findings at repository https://github.com/kalamoo/PPAudit, aiming to raise awareness within the VR community and pave the way for further research in this field.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
