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A Study of Privatized Synthetic Data Generation Using Discrete Cosine Transforms
International Journal of Advanced Computer Science and Applications
In order to comply with data confidentiality requirements, while meeting usability needs for researchers, entities are faced with the challenge of how to publish privatized data sets that preserve the statistical traits of the original data. One solution to this problem, is the generation of privatized synthetic data sets. However, during data privatization process, the usefulness of data, have a propensity to diminish even as privacy might be guaranteed. Furthermore, researchers havedoi:10.14569/ijacsa.2014.051107 fatcat:stn2vr5g4bestbivkgcax7pcpy