Anonimização de Streaming de Dados em DOCA
Resumo
Cenários online são cada vez mais comuns, propiciando grandes oportunidades de analise de dados. Frequentemente, esses dados contém informações sensíveis de indivíduos e, portanto, devem ser anonimizados para garantir sua privacidade. Este trabalho propõe DOCA, uma abordagem diferencialmente privada para publicação de streaming de dados em cenários não interativos utilizando uma estratégia de microagregação online para obtenção de melhor utilidade.
Palavras-chave:
Streaming de dados, informações sensíveis, microagregação
Referências
Bindschaedler, V., Shokri, R., and Gunter, C. A. (2017). Plausible deniability for privacy-preserving data synthesis. Proc. VLDB Endow., 10(5):481–492.
Cao, J., Carminati, B., Ferrari, E., and Tan, K. L. (2011). Castle: Continuously anonymizing data streams. IEEE Transactions on Dependable and Secure Computing, 8(3):337–352.
Chen, R., Mohammed, N., Fung, B. C. M., Desai, B. C., and Xiong, L. (2011). Publishing set-valued data via differential privacy. PVLDB, 4(11):1087–1098.
Dwork, C. and Roth, A. (2014). The algorithmic foundations of differential privacy. Found. Trends Theor. Comput. Sci., 9(3–4):211–407.
Backblaze (2017). The raw hard drive test data from 2017-01-01 to 2017-01-31. Online at https://www.backblaze.com/b2/hard-drive-test-data.html. acessed 2018-04-22.
Silva, J. A., Faria, E. R., Barros, R. C., Hruschka, E. R., Carvalho, A. C. P. L. F. d., and Gama, J. a. (2013). Data stream clustering: A survey. ACM Comput. Surv., 46(1):13:1–13:31.
Soria-Comas, J. and Domingo-Ferrer, J. (2017). Differentially private data sets based on microaggregation and record perturbation. In MDAI 2017, Kitakyushu, Japan, October, 2017, Proceedings, pages 119–131.
Soria-Comas, J., Domingo-Ferrer, J., Sanchez, D., and Martínez, S. (2014). Enhancing data utility in differential privacy via microaggregation-based k-anonymity. The VLDB Journal, 23(5):771–794.
Sweeney, L. (2002). k-anonymity: A model for protecting privacy. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 10(5):557–570.
Xu, J., Zhang, Z., Xiao, X., Yang, Y., Yu, G., and Winslett, M. (2013). Differentially private histogram publication. The VLDB Journal, 22(6):797–822.
Zhang, J., Cormode, G., Procopiuc, C. M., Srivastava, D., and Xiao, X. (2017). Privbayes: Private data release via bayesian networks. ACM Trans. Database Syst., 42(4):25:1–25:41
Cao, J., Carminati, B., Ferrari, E., and Tan, K. L. (2011). Castle: Continuously anonymizing data streams. IEEE Transactions on Dependable and Secure Computing, 8(3):337–352.
Chen, R., Mohammed, N., Fung, B. C. M., Desai, B. C., and Xiong, L. (2011). Publishing set-valued data via differential privacy. PVLDB, 4(11):1087–1098.
Dwork, C. and Roth, A. (2014). The algorithmic foundations of differential privacy. Found. Trends Theor. Comput. Sci., 9(3–4):211–407.
Backblaze (2017). The raw hard drive test data from 2017-01-01 to 2017-01-31. Online at https://www.backblaze.com/b2/hard-drive-test-data.html. acessed 2018-04-22.
Silva, J. A., Faria, E. R., Barros, R. C., Hruschka, E. R., Carvalho, A. C. P. L. F. d., and Gama, J. a. (2013). Data stream clustering: A survey. ACM Comput. Surv., 46(1):13:1–13:31.
Soria-Comas, J. and Domingo-Ferrer, J. (2017). Differentially private data sets based on microaggregation and record perturbation. In MDAI 2017, Kitakyushu, Japan, October, 2017, Proceedings, pages 119–131.
Soria-Comas, J., Domingo-Ferrer, J., Sanchez, D., and Martínez, S. (2014). Enhancing data utility in differential privacy via microaggregation-based k-anonymity. The VLDB Journal, 23(5):771–794.
Sweeney, L. (2002). k-anonymity: A model for protecting privacy. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 10(5):557–570.
Xu, J., Zhang, Z., Xiao, X., Yang, Y., Yu, G., and Winslett, M. (2013). Differentially private histogram publication. The VLDB Journal, 22(6):797–822.
Zhang, J., Cormode, G., Procopiuc, C. M., Srivastava, D., and Xiao, X. (2017). Privbayes: Private data release via bayesian networks. ACM Trans. Database Syst., 42(4):25:1–25:41
Publicado
25/08/2018
Como Citar
LEAL, Bruno C.; VIDAL, Israel C.; MACHADO, Javam C..
Anonimização de Streaming de Dados em DOCA. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 33. , 2018, Rio de Janeiro.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2018
.
p. 295-300.
ISSN 2763-8979.
DOI: https://doi.org/10.5753/sbbd.2018.22246.
