A proposal to increase data utility on Global Differential Privacy data based on data use predictions
Resumo
This paper presents ongoing research focused on improving the utility of data protected by Global Differential Privacy(DP) in the scenario of summary statistics. Our approach is based on predictions on how an analyst will use statistics released under DP protection, so that a developer can optimise data utility on further usage of the data in the privacy budget allocation. This novel approach can potentially improve the utility of data without compromising privacy constraints. We also propose a metric that can be used by the developer to optimise the budget allocation process.
Referências
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Fang, X., Yu, F., Yang, G., and Qu, Y. (2019). Regression analysis with differential privacy preserving. IEEE Access, 7:129353–129361.
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Yan, Y., Gao, X., Mahmood, A., Zhang, Y., Wang, S., and Sheng, Q. Z. (2020). An arithmetic differential privacy budget allocation method for the partitioning and publishing of location information. In 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), pages 1395–1401.
Fan, Z. and Xu, X. (2019). Apdpk-means: A new differential privacy clustering algorithm based on arithmetic progression privacy budget allocation. In 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS), pages 1737–1742.
Fang, X., Yu, F., Yang, G., and Qu, Y. (2019). Regression analysis with differential privacy preserving. IEEE Access, 7:129353–129361.
Hou, J., Li, Q., Meng, S., Ni, Z., Chen, Y., and Liu, Y. (2019). Dprf: A differential privacy protection random forest. IEEE Access, 7:130707–130720.
Luo, T., Pan, M., Tholoniat, P., Cidon, A., and Geambasu, R. (2021). Privacy budget scheduling.
Yan, Y., Gao, X., Mahmood, A., Zhang, Y., Wang, S., and Sheng, Q. Z. (2020). An arithmetic differential privacy budget allocation method for the partitioning and publishing of location information. In 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), pages 1395–1401.
Publicado
18/09/2023
Como Citar
NUNES, Henry C.; SILVA, Marlon P. da; NEU, Charles V.; ZORZO, Avelino F..
A proposal to increase data utility on Global Differential Privacy data based on data use predictions. In: SIMPÓSIO BRASILEIRO DE SEGURANÇA DA INFORMAÇÃO E DE SISTEMAS COMPUTACIONAIS (SBSEG), 23. , 2023, Juiz de Fora/MG.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 558-563.
DOI: https://doi.org/10.5753/sbseg.2023.233657.
