The Privacy Blanket of the Shuffle Model

Author:

Balle Borja,Bell James,Gascón Adrià,Nissim Kobbi

Publisher

Springer International Publishing

Reference25 articles.

1. Balle, B., Barthe, G., Gaboardi, M.: Privacy amplification by subsampling: tight analyses via couplings and divergences. In: Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, Montréal, Canada, 3–8 December 2018, pp. 6280–6290 (2018)

2. Balle, B., Bell, J., Gascón, A., Nissim, K.: The privacy blanket of the shuffle model. CoRR abs/1903.02837 (2019). http://arxiv.org/abs/1903.02837

3. Balle, B., Wang, Y.X.: Improving the Gaussian mechanism for differential privacy: analytical calibration and optimal denoising. In: Proceedings of the 35th International Conference on Machine Learning, ICML (2018)

4. Barthe, G., Gaboardi, M., Grégoire, B., Hsu, J., Strub, P.: Proving differential privacy via probabilistic couplings. In: Symposium on Logic in Computer Science (LICS), pp. 749–758 (2016)

5. Barthe, G., Köpf, B., Olmedo, F., Béguelin, S.Z.: Probabilistic relational reasoning for differential privacy. In: Symposium on Principles of Programming Languages (POPL), pp. 97–110 (2012)

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