Security problems on inference control for SUM, MAX, and MIN queries
Journal of the ACM (JACM)
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Further results on the security of partitioned dynamic statistical databases
ACM Transactions on Database Systems (TODS)
A munin network for the median nerve-a case study on loops
Applied Artificial Intelligence
Security-control methods for statistical databases: a comparative study
ACM Computing Surveys (CSUR)
Journal of Computer and System Sciences - Special issue on PODS 2000
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Auditing sum-queries to make a statistical database secure
ACM Transactions on Information and System Security (TISSEC)
Towards robustness in query auditing
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
A Bayesian Approach for on-Line Max Auditing
ARES '08 Proceedings of the 2008 Third International Conference on Availability, Reliability and Security
A Bayesian approach for on-line max and min auditing
PAIS '08 Proceedings of the 2008 international workshop on Privacy and anonymity in information society
Reasoning under Uncertainty in On-Line Auditing
PSD '08 Proceedings of the UNESCO Chair in data privacy international conference on Privacy in Statistical Databases
Auditing user queries in dynamic statistical databases
Information Sciences: an International Journal
Statistical analysis for comparison of the key representation database with the original database
International Journal of Business Information Systems
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In this paper we propose a method for on-line max auditing of dynamic statistical databases. The method extends the Bayesian approach presented in [2], [3] and [4] for static databases. A Bayesian network addresses disclosures based on probabilistic inferences that can be drawn from released data; we have developed algorithms to update the network whenever the database changes. In particular, we consider the case in which records are added or deleted, or some sensitive values change their value. The paper introduces the algorithms and discusses results of a preliminary set of of experimental trials.