Secure and Efficient Privacy Preserving Mechanism for Micro-Data
Access control mechanisms protect sensitive information from unauthorized users. However, sharing of sensitive information might lead to identity disclosure. A Privacy Protection Module (PPM) uses suppression and generalization of relational data to anonymize and satisfy privacy requirements, e.g., k-anonymity and l-diversity, against identity and attribute disclosure. In this paper, the authors propose an accuracy-constrained privacy-preserving access control framework where in the access control policies define selection predicates available to roles while the privacy requirement is to satisfy the k-anonymity or l-diversity.