Hybrid inferential security methods for statistical databases

Authors:
Steven C. Hansen
Affiliations:
University of St. Thomas
Venue:
ACM SIGAPP Applied Computing Review - Special issue on security
Year:
1995

Citing 7
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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

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Abstract

Memoryless inference control methods have been shown to provide effective means of reducing the amount of sensitive information released from a statistical database while maximizing the release of non-sensitive information. Early memoryless inference controls have the additional benefit of providing control at a low computation and storage cost. Two recent extensions to memoryless inference control allow the controls to release more non-sensitive information but do so at a greater cost in terms of computation and storage. This paper describes a proposed hybrid inference control method that can potentially maximize the release of information while holding down computation costs.