Please use this identifier to cite or link to this item:
|Title:||On addressing efficiency concerns in privacy-preserving mining|
|Citation:||DATABASE SYSTEMS FOR ADVANCED APPLICATIONS,2973,113-124|
|Abstract:||Data mining services require accurate input data for their results to be meaningful, but privacy concerns may influence users to provide spurious information. To encourage users to provide correct inputs, We recently proposed a data distortion scheme for association rule mining that simultaneously provides both privacy to the user and accuracy in the mining results. However, mining the distorted database can be orders of magnitude more time-consuming as compared to raining the original database. In this paper, we address this issue and demonstrate that by (a) generalizing the distortion process to perform symbol-specific distortion, (b) appropriately chooosing the distortion parameters, and (c) applying a variety of optimizations in the reconstruction process, runtime efficiencies that are well within an order of magnitude of undistorted mining can be achieved.|
|Appears in Collections:||Proceedings papers|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.