|Title:||An Effective and Efficient Inference Control System for Relational Database Queries|
|Abstract:||Protecting confidential information in relational databases while ensuring availability of public information at the same time is a demanding task. Unwanted information flows due to the reasoning capabilities of database users require sophisticated inference control mechanisms, since access control is in general not sufficient to guarantee the preservation of confidentiality. The policy-driven approach of Controlled Query Evaluation (CQE) turned out to be an effective means for controlling inferences in databases that can be modeled in a logical framework. It uses a censor function to determine whether or not the honest answer to a user query enables the user to disclose confidential information which is declared in form of a confidentiality policy. In doing so, CQE also takes answers to previous queries and the user’s background knowledge about the inner workings of the mechanism into account. Relational databases are usually modeled using first-order logic. In this context, the decision problem to be solved by the CQE censor becomes undecidable in general because the censor basically performs theorem proving over an ever growing user log. In this thesis, we develop a stateless CQE mechanism that does not need to maintain such a user log but still reaches the declarative goals of inference control. This feature comes at the price of several restrictions for the database administrator who declares the schema of the database, the security administrator who declares the information to be kept confidential, and the database user who sends queries to the database. We first investigate a scenario with quite restricted possibilities for expressing queries and confidentiality policies and propose an efficient stateless CQE mechanism. Due to the assumed restrictions, the censor function of this mechanism reduces to a simple pattern matching. Based on this case, we systematically enhance the proposed query and policy languages and investigate the respective effects on confidentiality. We suitably adapt the stateless CQE mechanism to these enhancements and formally prove the preservation of confidentiality. Finally, we develop efficient algorithmic implementations of stateless CQE, thereby showing that inference control in relational databases is feasible for actual relational database management systems under suitable restrictions.|
controlled query evaluation
|Appears in Collections:||LS 06 Informationssysteme und Sicherheit (ISSI), Information Engineering (IE)|
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