The rank based proximity swap has been suggested as a data masking mechanism for numerical data. Recently, more sophisticated procedures for masking numerical data that are based on the concept of “shuffling” the data have been proposed. In this study, we compare and contrast the performance of the swapping and shuffling procedures. The results indicate that the shuffling procedures perform better than data swapping both in terms of data utility and disclosure risk.
CITATION STYLE
Muralidhar, K., Sarathy, R., & Dandekar, R. (2006). Why swap when you can shuffle? A comparison of the proximity swap and data shuffle for numeric data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4302, pp. 164–176). Springer Verlag. https://doi.org/10.1007/11930242_15
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