In today's highly connected society, we are constantly asked to provide personal information to retailers, voter surveys, medical professionals, and other data collection efforts. The collected data is stored in large data warehouses. Organisations and statistical agencies share and use this data to facilitate research in public health, economics, sociology, etc. However, this data contains sensitive information about individuals, which can result in identity theft, financial loss, stress and depression, embarrassment, abuse, etc. Therefore, one must ensure rigorous management of individuals' privacy. We propose, an advanced data privacy management architecture composed of three layers. The data management layer consists of de-identification and anonymisation, the access management layer for re-enforcing data access based on the concepts of Role-Based Access Control and the Chinese Wall Security Policy, and the roles layer for regulating different users. The proposed system architecture is validated on healthcare datasets.

翻译：在当今高度互联的社会中，我们不断被要求向零售商、选民调查、医疗专业人员及其他数据收集工作提供个人信息。收集到的数据被存储在大型数据仓库中。组织和统计机构共享并使用这些数据，以促进公共卫生、经济学、社会学等领域的研究。然而，这些数据包含个人敏感信息，可能导致身份盗窃、经济损失、压力与抑郁、尴尬、虐待等问题。因此，必须严格管理个人隐私。我们提出了一种先进的数据隐私管理架构，由三个层次组成。数据管理层包括去标识化和匿名化，访问管理层基于角色访问控制与中国墙安全策略的概念强化数据访问，角色层用于规范不同用户。所提出的系统架构在医疗数据集上得到了验证。