We propose a new method to re-identify anonymized data by using Euclidean distance between the original record and the anonymized record and evaluate the accuracy of the proposed method. In order to clarify performance of several anonymization methods used in the competition of the PWSCUP2015, we examine each of single methods and attempt to estimate the accuracy of the combination of some methods.
CITATION STYLE
Ito, S., & Kikuchi, H. (2018). Risk of re-identification based on euclidean distance in anonymized data pwscup2015. In Lecture Notes on Data Engineering and Communications Technologies (Vol. 7, pp. 901–913). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-65521-5_81
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