Using unknowns to prevent discovery of association rules

被引：19

作者：

Saygin, Y ^{[1
]}

Verykios, VS ^{[1
]}

Clifton, C ^{[1
]}

机构：

[1] Purdue Univ, Dept Comp Sci, W Lafayette, IN 47907 USA

来源：

SIGMOD RECORD | 2001年 / 30卷 / 04期

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Data mining technology has given us new capabilities to identify correlations in large data sets. This introduces risks when the data is to be made public, but the correlations are private. We introduce a method for selectively removing individual values from a database to prevent the discovery of a set of rules, while preserving the data for other applications. The efficacy and complexity of this method are discussed. We also present an experiment showing an example of this methodology.

引用

页码：45 / 54

页数：10

共 8 条

[1] Agrawal D., 2001, Proceedings of the 20th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, P247, DOI DOI 10.1145/375551.375602
[2] AGRAWAL R, 2000, P SIGMOD C, P45
[3] Atallah M., 1999, PROC 1999 WORKSHOP K, P45, DOI DOI 10.1109/KDEX.1999.836532
[4] Chang LW, 1999, NEW SECURITY PARADIGMS WOEKSHOP, PROCEEDINGS, P82
[5] Clifton C., 2000, J COMPUTER SECURITY, V8
[6] ELENA D, 2001, IN PRESS P INF HID W
[7] Protecting databases from inference attacks
Hinke, TH
Delugach, HS
Wolf, RP
[J]. COMPUTERS & SECURITY, 1997, 16 (08) : 687 - 708
[8] VERYKLOS VS, 2000, UNPUB IEEE T KNOWLED

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