Security checking in relational database management systems augmented with inference engines
Computers and Security
ILIAD: an integrated laboratory for inference analysis and detection
Proceedings of the ninth annual IFIP TC11 WG11.3 working conference on Database security IX : status and prospects: status and prospects
Minimal data upgrading to prevent inference and association attacks
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Design of LDV: A Multilevel Secure Relational Database Management
IEEE Transactions on Knowledge and Data Engineering
Inference in MLS Database Systems
IEEE Transactions on Knowledge and Data Engineering
The inference problem: a survey
ACM SIGKDD Explorations Newsletter
Data Level Inference Detection in Database Systems
CSFW '98 Proceedings of the 11th IEEE workshop on Computer Security Foundations
Journal of Computer and System Sciences - Special issue on PODS 2000
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
A data-level database inference detection system
A data-level database inference detection system
New paradigm of inference control with trusted computing
Proceedings of the 21st annual IFIP WG 11.3 working conference on Data and applications security
Inference aggregation detection in database management systems
SP'88 Proceedings of the 1988 IEEE conference on Security and privacy
Satisfiability modulo theories: introduction and applications
Communications of the ACM
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In secure data management the inference problem occurs when data classified at a high security level becomes inferrible from data classified at lower levels. We present a model-theoretic approach to this problem that captures the epistemic state of the database user as a set of possible worlds or models. Privacy is enforced by requiring the existence of k 1 models assigning distinct values to sensitive attributes, and implemented via model counting. We provide an algorithm mechanizing this process and show that it is sound and complete for a large class of queries.