Enhancing the Security of Statistical Databases with a Question-Answering System and a Kernel Design

Özsoyoǧlu, Gültekin; Chin, Francis Y. L.

doi:10.1109/tse.1982.235252

Cited by 12 publications

(2 citation statements)

References 27 publications

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“…Another approach may be to define formally type R inferences and use a theorem prover to decide about the inferred knowledge and the disclosed information. In [26], this approach ' 129 q which uses a question-answering system to enhance the security of the SDB, is outlined.…”

Section: Protection Requirements For Different Statistical Queriesmentioning

confidence: 99%

Statistical database design

Chin

Özsoyoǧlu

1981

ACM Trans. Database Syst.

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The security problem of a statistical database is to limit the use of the database so that no sequence of statistical queries is sufficient to deduce confidential or private information. In this paper it is suggested that the problem be investigated at the conceptual data model level. The design of a statistical database should utilize a statistical security management facility to enforce the security constraints at the conceptual model level. Information revealed to users is well defined in the sense that it can at most be reduced to nondecomposable information involving a group of individuals. In addition, the design also takes into consideration means of storing the query information for auditing purposes, changes in the database, users' knowledge, and some security measures.

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Section: Protection Requirements For Different Statistical Queriesmentioning

confidence: 99%

Statistical database design

Chin

Özsoyoǧlu

1981

ACM Trans. Database Syst.

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“…The main approaches to this problem involve perturbing the data so as to maintain their statistical characteristics but prevent their compromise [13,11,16], to perturb the responses for the same purpose, [2,8], to restrict the size or overlap of the statistical queries [10,9], or, finally (and closer to our concerns here), to audit the statistical queries in order to determine when enough information has been given out so that compromise becomes possible [3,4,5,12].…”

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confidence: 99%

Auditing Boolean attributes

Kleinberg

Papadimitriou

Raghavan

2000

Proceedings of the Nineteenth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems - PODS '00

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We study the problem of auditing databases which support statistical sum queries to protect the security of sensitive information; we focus on the special case in which the sensitive information is Boolean. Principles and techniques developed for the security of statistical databases in the case of continuous attributes do not apply here. We prove certain strong complexity results suggesting that there is no general efficient solution for the auditing problem in this case. We propose two efficient algorithms: The first is applicable when the sum queries are one-dimensional range queries (we prove that the problem is NP-hard even in the two-dimensional case). The second is an approximate algorithm that maintains security, although it may be too restrictive. Finally, we consider a "dual" variant, with continuous data but an aggregate function that is combinatorial in nature. Specifically, we provide algorithms for two natural definitions of the auditing condition when the aggregate function is max.

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