用量化方法提升数据保护合规性，让隐私风险可衡量、可决策。
A Personal data Value at Risk Approach
- 从数据控制方视角出发，构建可量化的数据保护风险评估框架。
- 将专家判断与数据分析结合，实现对隐私影响的精准量化评估。
- 适合关注GDPR合规落地、希望摆脱经验主义的企业与安全团队。
若数据保护的核心脆弱性在于风险管理，会如何？数据保护融合了数据保护法、信息安全与风险管理三大学科，但针对数据保护风险管理的研究极少，当前实践普遍存在主观性和表面化问题。由于GDPR规定了‘应做什么’，却未说明‘如何做’，合规路径仍处于灰色地带，普遍依赖经验法则。而风险管理的核心目标是降低不确定性以支持科学决策，因此数据保护必须与数据主体权利受损的可能性评估紧密关联。本文提出一种面向数据控制方的、基于风险的数据保护合规量化方法，旨在推动思维转变：通过数据保护分析、定量风险评估及专家意见校准，改进数据保护影响评估（DPIA）的有效性。
原文摘要 · Abstract (English)
What if the main data protection vulnerability is risk management? Data Protection merges three disciplines: data protection law, information security, and risk management. Nonetheless, very little research has been made on the field of data protection risk management, where subjectivity and superficiality are the dominant state of the art. Since the GDPR tells you what to do, but not how to do it, the solution for approaching GDPR compliance is still a gray zone, where the trend is using the rule of thumb. Considering that the most important goal of risk management is to reduce uncertainty in order to take informed decisions, risk management for the protection of the rights and freedoms of the data subjects cannot be disconnected from the impact materialization that data controllers and processors need to assess. This paper proposes a quantitative approach to data protection risk-based compliance from a data controllers perspective, with the aim of proposing a mindset change, where data protection impact assessments can be improved by using data protection analytics, quantitative risk analysis, and calibrating expert opinions.
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