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Synthetic Data Perturbation Techniques for Privacy Preservation in Association Rule Mining

Publication Type : Conference Proceedings

Publisher : National Conference on Computing Communication and Information Technology

Authors : Dr. Anju Pillai S.

Source : National Conference on Computing Communication and Information Technology, Volume 11 (2013)

Url : https://www.researchgate.net/publication/325961348_Synthetic_Data_Perturbation_Techniques_for_Privacy_Preservation_in_Association_Rule_Mining

Campus : Chennai

School : Department of Computer Science and Engineering, School of Engineering

Department : Computer Science

Year : 2013

Abstract : In recent, data mining is becoming a popular analysis tool to extract knowledge from collection of large amount of data. The protection of the confidentiality of sensitive information in a database becomes a critical issue when releasing data to outside parties. Association analysis is a powerful and popular tool for discovering relationships hidden in large data sets. These process increases the legal responsibility of the parties. So, it is severe to reliably protect their data due to legal and customer concerns. In this paper, a review of the state-of-the-art methods of data perturbation techniques for privacy preservation is presented.

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