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

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Advances in Network-Based Information Systems (NBiS 2017)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 7))

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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.

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References

  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)

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  3. Sweeny, L.: \(k\)-anonymity. Int. J. Uncertainty Fuzziness Knowl. Based Syst. 10, 571–588 (2002)

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  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)

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Acknowledgements

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

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Authors and Affiliations

  1. Graduate School, Meiji University, Tokyo, 164-8525, Japan

    Satoshi Ito & Hiroaki Kikuchi

Authors
  1. Satoshi Ito
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  2. Hiroaki Kikuchi
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Corresponding author

Correspondence to Satoshi Ito .

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Editors and Affiliations

  1. Department of Information and Communication Engineering, Faculty of Information Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Rissho University, Tokyo, Japan

    Tomoya Enokido

  3. Hosei University, Tokyo, Japan

    Makoto Takizawa

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Ito, S., Kikuchi, H. (2018). Risk of Re-Identification Based on Euclidean Distance in Anonymized Data PWSCUP2015 . In: Barolli, L., Enokido, T., Takizawa, M. (eds) Advances in Network-Based Information Systems. NBiS 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-319-65521-5_81

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  • DOI: https://doi.org/10.1007/978-3-319-65521-5_81

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65520-8

  • Online ISBN: 978-3-319-65521-5

  • eBook Packages: EngineeringEngineering (R0)

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