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arXiv 2603.23935cs.CR
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谷歌Play数据安全披露的实证分析:移动游戏应用隐私指标的一致性研究

An Empirical Analysis of Google Play Data Safety Disclosures: A Consistency Study of Privacy Indicators in Mobile Gaming Apps

Umm Al-Qura University(乌姆古拉大学)

Bakheet Aljedaani

AI总结:

本研究通过分析41款移动游戏应用,探讨开发者报告的数据安全披露与APK中提取的隐私指标一致性,发现设备ID披露一致性较高,而位置、个人信息和数据共享存在显著不一致。

摘要:

谷歌Play市场引入了数据安全板块以提高移动应用收集、分享和保护用户数据的透明度。此机制要求开发者披露隐私和安全实践,但这些披露的可靠性依赖于开发者自报,存在准确性问题。本研究调查了开发者报告的数据安全披露与从Android应用程序包(APK)中提取的隐私指标之间的一致性。对41款移动游戏应用的数据集进行了实证分析。采用静态分析方法从APK文件中提取关键隐私指标,包括设备ID、数据共享、个人信息访问和位置访问。这些指标通过结构化一致性评估框架与Google Play数据安全标签中相应的披露进行系统性比较。结果揭示了隐私类别中不一致性的不同水平。设备ID披露显示相对较高的一致性(87.8%),而其他指标存在显著不匹配。与儿童导向和一般受众应用的比较分析显示相似的不匹配模式。卡方统计检验表明这些差异不具有统计学意义,表明披露不一致并非与应用类别相关,而是反映更广泛的生态系统层面挑战。这些发现突显了当前市场透明机制可靠性的局限性,并强调了改进验证和验证方法以确保移动应用生态系统中准确隐私报告的必要性。

英文摘要:

The Google Play marketplace has introduced the Data Safety section to improve transparency regarding how mobile applications (apps) collect, share, and protect user data. This mechanism requires developers to disclose privacy and security-related practices. However, the reliability of these disclosures remains dependent on developer self-reporting, raising concerns about their accuracy. This study investigates the consistency between developer-reported Data Safety disclosures and observable privacy indicators extracted from Android Application Packages (APKs). An empirical analysis was conducted on a dataset of 41 mobile gaming apps. A static analysis approach was used to extract key privacy indicators from APK files, including device IDs, data sharing, personal information access, and location access. These indicators were systematically compared with the corresponding disclosures reported in the Google Play Data Safety labels using a structured consistency evaluation framework. The results revealed varying levels of agreement across privacy categories. Device ID disclosures demonstrated relatively high consistency (87.8%), whereas other indicators exhibited substantial mismatches. Location-related disclosures showed the highest inconsistency rate (56.1%), followed by personal information and data sharing. Comparative analysis between children-oriented and general-audience apps revealed similar mismatch patterns. Also, Chi-square statistical tests indicate that these differences are not statistically significant, suggesting that disclosure inconsistencies are not associated with app category but instead reflect broader ecosystem-level challenges. These findings highlight limitations in the reliability of current marketplace transparency mechanisms and emphasize the need for improved validation and verification approaches to ensure accurate privacy reporting in mobile app ecosystems.

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。

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