Pervasive data collection by Smart Home Devices (SHDs) demands robust Privacy Protection Mechanisms (PPMs). The effectiveness of many PPMs, particularly user-facing controls, depends on user awareness and adoption, which are shaped by manufacturers' public documentations. However, the landscape of academic proposals and commercial disclosures remains underexplored. To address this gap, we investigate: (1) What PPMs have academics proposed, and how are these PPMs evaluated? (2) What PPMs do manufacturers document and what factors affect these documentation? To address these questions, we conduct a two-phase study, synthesizing a systematic review of 117 academic papers with an empirical analysis of 86 SHDs' publicly disclosed documentations. Our review of academic literature reveals a strong focus on novel system- and algorithm-based PPMs. However, these proposals neglect deployment barriers (e.g., cost, interoperability), and lack real-world field validation and legal analysis. Concurrently, our analysis of commercial SHDs finds that advanced academic proposals are absent from public discourse. Industry postures are fundamentally reactive, prioritizing compliance via post-hoc data management (e.g., deletion options), rather than the preventative controls favored by academia. The documented protections correspondingly converge on a small set of practical mechanisms, such as physical buttons and localized processing. By synthesizing these findings, we advocate for research to analyze challenges, provide deployable frameworks, real-world field validation, and interoperability solutions to advance practical PPMs.
翻译:智能家居设备(SHDs)的普遍数据收集要求强大的隐私保护机制(PPMs)。许多PPMs(尤其是面向用户的控制措施)的有效性取决于用户意识和采用程度,而这些受制造商公开文档的影响。然而,学术提案与商业披露的现状仍缺乏深入探索。为填补这一空白,我们研究:(1)学术界提出了哪些PPMs,这些机制如何被评估?(2)制造商记录了哪些PPMs,影响这些文档的因素是什么?为解决这些问题,我们开展了一项两阶段研究:系统综述了117篇学术论文,并对86款SHDs公开披露的文档进行了实证分析。学术文献综述显示,研究重点集中于新颖的系统和算法基础PPMs。然而,这些提案忽视了部署障碍(如成本、互操作性),缺乏真实场景的实地验证和法律分析。同时,对商业SHDs的分析发现,先进的学术提案未出现在公共讨论中。行业立场本质上是反应式的,优先通过事后数据管理(如删除选项)实现合规,而非学术界青睐的预防性控制。相应的文档化保护措施集中于少量实用机制,如物理按钮和本地化处理。通过综合这些发现,我们倡导研究应分析挑战、提供可部署框架、真实场景实地验证及互操作性解决方案,以推动实用PPMs的发展。