K-Anonymity technique for privacy protection: a proof of concept study

  • Italo Santos USP
  • Emanuel Coutinho UFC
  • Leonardo Moreira UFC

Resumo


Privacy is a concept directly related to people's interest in maintaining personal space without the interference of others. In this paper, we focus on study the k-anonymity technique since many generalization algorithms are based on this privacy model. Due to this, we develop a proof of concept that uses the k-anonymity technique for data anonymization to anonymize data raw and generate a new file with anonymized data. We present the system architecture and detailed an experiment using the adult data set which has sensitive information, where each record corresponds to the personal information for a person. Finally, we summarize our work and discuss future works.

Referências

Camenisch, J., Fischer-Hübner, S., and Rannenberg, K. (2011). Privacy and identity management for life. Springer Science & Business Media.

Cormode, G. and Srivastava, D. (2009). Anonymized data: generation, models, usage. In Proceedings of the 2009 ACM SIGMOD International Conference on Management of data, pages 1015–1018. ACM.

Fredj, F. B., Lammari, N., and Comyn-Wattiau, I. (2014). Characterizing generalization algorithms-rst guidelines for data publishers. In KMIS 2014-International Conference on Knowledge Management and Information Sharing, page pp.

Prasser, F., Kohlmayer, F., Lautenschläger, R., and Kuhn, K. A. (2014). Arx-a comprehensive tool for anonymizing biomedical data. In AMIA Annual Symposium Proceedings, volume 2014, page 984. American Medical Informatics Association.

Samarati, P. (2001). Protecting respondents identities in microdata release. IEEE trans- actions on Knowledge and Data Engineering, 13(6):1010–1027.

Santos, íI. O., Coutinho, E. F., and Moreira, L. O. (2018). Smdanonymizer: a web tool for data anonymization. In 6th International Workshop on ADVANCEs in ICT INfrastructures and Services (ADVANCE 2018), Santiago - Chile.

Sweeney, L. (2002). k-anonymity: A model for protecting privacy. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 10(05):557–570.

Wong, R., Li, J., Fu, A. W.-C., and Wang, K. (2006). K-anonymity: An enhanced k-anonymity model for privacy preserving data publishing. In KDD.
Publicado
02/09/2019
SANTOS, Italo; COUTINHO, Emanuel; MOREIRA, Leonardo. K-Anonymity technique for privacy protection: a proof of concept study. In: SIMPÓSIO BRASILEIRO DE SEGURANÇA DA INFORMAÇÃO E DE SISTEMAS COMPUTACIONAIS (SBSEG), 19. , 2019, São Paulo. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2019 . p. 391-396. DOI: https://doi.org/10.5753/sbseg.2019.13987.

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