Information Protection in Dynamic Statistical Databases

A statistical database (SDB) is a database that contains sensitive records describing individuals but only statistical information is available. There are many inference control methods proposed to protect SDBs. In this article, we will briefly introduce three general approaches: conception, perturbation, and query restriction approaches. In addition, six criteria are also introduced to evaluate the features of these mechanisms. However, in practice, many SDBs are dynamically updated. This feature restricts the use of many inference control methods. Thus, in the rest of the article, we will present an efficient audit scheme, which is a query-restriction-based security-control method for protecting dynamic SDBs. This scheme guarantees the security of SDBs and needs less time and storage requirements than the traditional schemes while database systems are dynamically updated.