A well known method for privacy-preserving data mining is that of randomization. In randomization, we add noise to the data so that the behavior of the individual records is masked. However, the aggregate behavior of the data distribution can be reconstructed by subtracting out the noise from the data. The reconstructed distribution is often sufficient for a variety of data mining tasks such as classification. In this chapter, we will provide a survey of the randomization method for privacy-preserving data mining.
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Aggarwal, C.C., Yu, P.S. (2008). A Survey of Randomization Methods for Privacy-Preserving Data Mining. In: Aggarwal, C.C., Yu, P.S. (eds) Privacy-Preserving Data Mining. Advances in Database Systems, vol 34. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-70992-5_6
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