揭示隐私威胁建模的复杂性：概念性隐私分析层次
Unraveling Privacy Threat Modeling Complexity: Conceptual Privacy Analysis Layers
AI总结：
本文针对隐私威胁分析中“如何发现威胁”不清晰的问题，提出功能、生态系统、业务上下文和环境四个概念层次来结构化隐私分析支持，以提升分析过程的可操作性。
摘要：
分析软件产品中的隐私威胁是软件开发中确保系统尊重隐私的必要组成部分，然而这仍然远非一项简单的活动。尽管过去十年中取得了许多进展，但这些进展往往侧重于描述威胁“是什么”。目前尚不完全清楚的是“如何”真正发现这些威胁。隐私是一个复杂的领域。我们提出使用四个概念层次（功能、生态系统、业务上下文和环境）来捕捉这种隐私复杂性。这些层次可以作为一个框架，以更具体和可操作的方式构建和明确隐私分析支持，从而提高分析过程的适用性。
英文摘要：
Analyzing privacy threats in software products is an essential part of software development to ensure systems are privacy-respecting; yet it is still a far from trivial activity. While there have been many advancements in the past decade, they tend to focus on describing 'what' the threats are. What isn't entirely clear yet is 'how' to actually find these threats. Privacy is a complex domain. We propose to use four conceptual layers (feature, ecosystem, business context, and environment) to capture this privacy complexity. These layers can be used as a frame to structure and specify the privacy analysis support in a more tangible and actionable way, thereby improving applicability of the analysis process.
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。
