Investigating Bystander Privacy in Chinese Smart Home Apps

2026-02-09

AI Summary

This study addresses the long-standing neglect of bystander privacy—such as that of visitors—in Chinese smart home applications, where gaps persist between policy and practice alongside opaque data-sharing practices. Focusing specifically on the Chinese context, the research employs a mixed-methods approach to systematically analyze 49 applications, integrating privacy policy textual analysis, user interface evaluation, comparison with Apple App Store privacy labels, and verification of data flow traceability. Findings reveal that while most apps appear nominally compliant, they普遍 lack substantive privacy safeguards for bystanders, and their declared privacy labels often significantly diverge from actual data practices. In response, this work proposes an inclusive privacy-by-design framework tailored for non-Western markets, emphasizing actionable pathways to enhance transparency and trustworthiness.

Technology Category

• Machine Learning: Privacy
• Application Domains: Other Applications
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy

Application Category

• Security and Privacy: Privacy-enhancing technologies
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Responsible Web: Data and user privacy-enhancing technologies for the Web

Abstract

Bystander privacy in smart homes has been widely studied in Western contexts, yet it remains underexplored in non-Western countries such as China. In this study, we analyze 49 Chinese smart home apps using a mixed-methods approach, including privacy policy review, UX/UI evaluation, and assessment of Apple App Store privacy labels. While most apps nominally comply with national regulations, we identify significant gaps between written policies and actual implementation. Our traceability analysis highlights inconsistencies in data controls and a lack of transparency in data-sharing practices. Crucially, bystander privacy -- particularly for visitors and non-user individuals -- is largely absent from both policy documents and interface design. Additionally, discrepancies between privacy labels and actual data practices threaten user trust and undermine informed consent. We provide design recommendations to strengthen bystander protections, improve privacy-oriented UI transparency, and enhance the credibility of privacy labels, supporting the development of inclusive smart home ecosystems in non-Western contexts.

Problem

• bystander privacy
• smart home apps
• privacy policy
• data transparency
• informed consent

Innovation

• bystander privacy
• smart home apps
• privacy policy compliance
• privacy labels
• mixed-methods analysis