Obtaining $(\epsilon,\delta)$-differential privacy guarantees when using a Poisson mechanism to synthesize contingency tables
<|reference_start|>Obtaining $(\epsilon,\delta)$-differential privacy guarantees when using a Poisson mechanism to synthesize contingency tables: We show that differential privacy type guarantees can be obtained when using a Poisson synthesis mechanism to protect counts in contingency tables. Specifically, we show how to obtain $(\epsilon, \delta)$-probabilistic differential privacy guarantees via the Poisson distribution's cumulative distribution function. We demonstrate this empirically with the synthesis of an administrative-type confidential database.<|reference_end|>
@article{jackson2024obtaining,
    title={Obtaining $(\epsilon,\delta)$-differential privacy guarantees when using
  a Poisson mechanism to synthesize contingency tables},
    author={James Jackson and Robin Mitra and Brian Francis and Iain Dove},
    journal={arXiv preprint arXiv:2407.00417},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.00417},
    primaryClass={cs.CR stat.ME}
}