Secure databases: protection against user influence
ACM Transactions on Database Systems (TODS)
The tracker: a threat to statistical database security
ACM Transactions on Database Systems (TODS)
Security in statistical databases for queries with small counts
ACM Transactions on Database Systems (TODS)
A model of statistical database their security
ACM Transactions on Database Systems (TODS)
Inference from statistical data bases.
Inference from statistical data bases.
Further results on the security of partitioned dynamic statistical databases
ACM Transactions on Database Systems (TODS)
Security-control methods for statistical databases: a comparative study
ACM Computing Surveys (CSUR)
A universal-scheme approach to statistical databases containing homogeneous summary tables
ACM Transactions on Database Systems (TODS)
Compromising statistical databases responding to queries about means
ACM Transactions on Database Systems (TODS)
MULTISAFE—a modular multiprocessing approach to secure database management
ACM Transactions on Database Systems (TODS)
The tracker: a threat to statistical database security
ACM Transactions on Database Systems (TODS)
Secure statistical databases with random sample queries
ACM Transactions on Database Systems (TODS)
Security of statistical databases: multidimensional transformation
ACM Transactions on Database Systems (TODS)
ACM Computing Surveys (CSUR)
Formal Models for Computer Security
ACM Computing Surveys (CSUR)
Randomizing, A Practical Method for Protecting Statistical Databases Against Compromise
VLDB '82 Proceedings of the 8th International Conference on Very Large Data Bases
Disclosure risk measures for the sampling disclosure control method
Proceedings of the 2004 ACM symposium on Applied computing
A security model for the statistical database problem
SSDBM'83 Proceedings of the 2nd international workshop on Proceedings of the Second International Workshop on Statistical Database Management
Statistical databases: their model, query language and security
SSDBM'83 Proceedings of the 2nd international workshop on Proceedings of the Second International Workshop on Statistical Database Management
Effective inference control mechanisms for securing statistical databases
AFIPS '81 Proceedings of the May 4-7, 1981, national computer conference
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A database is compromised if a user can determine the data elements associated with keys which he did not know previously. If it is possible, compromise can be achieved by posing a finite set of queries over sets of data elements and employing initial information to solve the resulting system of equations. Assuming the allowable queries are linear, that is, weighted sums of data elements, we show how compromise can be achieved and we characterize the maximal initial information permitted of a user in a secure system. When compromise is possible, the initial information and the number of queries required to achieve it is surprisingly small.