  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.
