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.
T. Ravi and R. Prasanna Kumar, “Data Perturbation Techniques for Privacy Preservation in Association Rule Mining”, Australian Journal of Basic and Applied Sciences, vol. 9, no. 20, pp. 220-227, 2015.