Privacy preserving for relational database using restricted hybrid model

Revolutionary expansion of Internet and online services has enabled hospital and popular companies to publish data for research. Publishing data contains confidential information which needs to be protected. To meet this privacy concern, direct identity of related User is neglected while publishing. Although these measures are not enough, as confidential information can be derived from released data using re-identity concept. Privacy preserving mechanism is used to hinder the individual's identity at the time of publishing. Next challenge is access privilege which categorizes only authorized user to access restricted data. To address this issue Access Control Mechanism (ACM) is integrated which provides robustness and security. This proposed work is used to provide accurate data by collaborating both privacy and access control mechanism. Our methodology for privacy includes anonymization technique applied to grouped data. In the proposed method, privacy preservation is achieved through generalization of quasi identifier by setting range values. Security is achieved by allowing user to get limited output for a given query in the form of static count with specific attributes. Access control is implemented by adding constrain on input query based on location.