Sensitive Data Hiding Through Extending Database

Provided by: Universal Insurance Managers, Inc.
Topic: Big Data
Format: PDF
In this paper, the authors propose a novel, exact border-based approach that provides an optimal solution for the hiding of sensitive frequent item sets by minimally extending the original database by a synthetically generated database part-the database extension, formulating the creation of the database extension as a constraint satisfaction problem, mapping the constraint satisfaction problem to an equivalent binary integer programming problem, exploiting underutilized synthetic transactions to proportionally increase the support of non-sensitive item sets, minimally relaxing the constraint satisfaction problem to provide an approximate solution close to the optimal one when an ideal solution does not exist, and using a partitioning in the universe of the items to increase the efficiency of the proposed hiding algorithm.

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