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Exact Knowledge Hiding through Database Extension
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DOI：10.1109/TKDE.2008.199.png)
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摘要
En 中文
In this paper, we propose a novel, exact border-based approach that provides an optimal solution for the hiding of sensitive frequent item sets by 1) minimally extending the original database by a synthetically generated database part-the database extension, 2) formulating the creation of the database extension as a constraint satisfaction problem, 3) mapping the constraint satisfaction problem to an equivalent binary integer programming problem, 4) exploiting underutilized synthetic transactions to proportionally increase the support of nonsensitive item sets, 5) minimally relaxing the constraint satisfaction problem to provide an approximate solution close to the optimal one when an ideal solution does not exist, and 6) using a partitioning in the universe of the items to increase the efficiency of the proposed hiding algorithm. Extending the original database for sensitive item set hiding is proved to provide optimal solutions to an extended set of hiding problems compared to previous approaches and to provide solutions of higher quality. Moreover, the application of binary integer programming enables the simultaneous hiding of the sensitive item sets and thus allows for the identification of globally optimal solutions.
Keyword:
Privacy preserving data mining
knowledge hiding
association rule mining
binary integer programming
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10.4
论文数:
6.8K
被引数:
3.2W
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