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Risk of Re-Identification Based on Euclidean Distance in Anonymized Data PWSCUP2015

  • Satoshi ItoEmail author
  • Hiroaki Kikuchi
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 7)

Abstract

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.

Notes

Acknowledgements

We thank NSC for synthesized micro data and thank all participants of PWSCUP2015 for the anonymized data to study.

References

  1. 1.
    Kikuchi, H., Yamaguchi, T., Hamada, K., Yamaoka, Y., Oguri, H., Sakuma, J.: What is the best anonymization method? - a study from the data anonymization competition Pwscup 2015. In: Data Privacy Management Security Assurance (DPM2016). LNCS, vol. 9963, pp. 230–237 (2016)Google Scholar
  2. 2.
    Kikuchi, H., Yamaguchi, T., Hamada, K., Yamaoka, Y., Oguri, H., Sakuma, J.: Ice and fire: quantifying the risk of re-identification and utility in data anonymization. In: 2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA), Crans-Montana, pp. 1035-1042 (2016)Google Scholar
  3. 3.
    Sweeny, L.: \(k\)-anonymity. Int. J. Uncertainty Fuzziness Knowl. Based Syst. 10, 571–588 (2002)CrossRefGoogle Scholar
  4. 4.
    Akiyama, H., Yamaguchi, K., Ito, S., Hoshino, N., Goto, T.: Usage and development of educational pseudo micro-data -sampled from national survey of family income and expenditure in 2004. Technical report of the National Statistics Center (NSTAC), vol. 16, pp. 1–43 (2012). (in Japanese)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Graduate SchoolMeiji UniversityTokyoJapan

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