Toward privacy-preserving database management systems — Access control and data anonymization
Abstract
In this thesis, we identify basic requirements for privacy-preserving DBMS and focus on two core techniques, namely purpose-based access control and data anonymization, that are essential to address some of the requirements. Specifically, purpose-based access control enables DBMS to tightly control data access with respect to privacy requirements and preferences, and data anonymization provides a way to guarantee privacy protection in data itself even if the control of access is not feasible. We present formal models and develop mechanisms for realizing such models. In addition, we introduce two conceptual models, micro-view and integrity-control, which are designed to enhance data utility and integrity, respectively.
Degree
Ph.D.
Advisors
Li, Purdue University.
Subject Area
Computer science
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