Purpose Based Access Control for Privacy Protection in Database Systems

Abstract

The development of privacy-preserving data management techniques has been the focus of intense research in the last few years. Such research has resulted in important notions and techniques, such as the notions of Hippocratic database systems and k-anonymity, and various privacy-preserving data mining techniques. However, much work still needs to be carried out to develop high assurance privacy-preserving database management systems. An important requirement in the development of such systems is the need of providing comprehensive and accurate privacy-related metadata, such as data usage purposes. Such metadata represent the core of access control mechanisms specifically tailored towards privacy. In this talk we address such issue. We present a comprehensive approach for privacy preserving access control based on the notion of purpose. Purpose information associated with a given data element specifies the intended use of the data element. Purpose information represents an important form of metadata, because data usage purpose is very often part of privacy policies, such as the case of policies expressed according to P3P. A key feature of our model is that it allows multiple purposes to be associated with each data element and it also supports explicit prohibitions, thus allowing privacy officers to specify that some data should not be used for certain purposes. Another important issue to be addressed is the granularity of data labeling, that is, the units of data with which purposes can be associated. We address this issue in the context of relational databases and propose four different labeling schemes, each providing a different granularity. In the paper we also propose an approach to representing purpose information, which results in very low storage overhead, and we exploit query modification techniques to support data access control based on purpose information. We conclude the talk by outlining future work that includes the application of our purpose management techniques to complex data and its integration into RBAC.

Keywords

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