LaPSuS—A Lattice-Based Private Stream Aggregation Scheme Under Scrutiny
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-71073-5_11
Reference16 articles.
1. Becker, D., Guajardo, J., Zimmermann, K.-H.: Revisiting private stream aggregation: lattice-based PSA. In: NDSS 2018. The Internet Society (2018). https://www.ndss-symposium.org/wp-content/uploads/2018/02/ndss201802B-3Beckerpaper.pdf
2. Becker, D., Merchan, J.G.: Post-quantum secure private stream aggregation. US Patent 10,630,655 (2020). https://patents.google.com/patent/US10630655B2/en
3. Benhamouda, F., Joye, M., Libert, B.: A new framework for privacypreserving aggregation of time-series data. In: ACM Transactions on Information and System Security (TISSEC), vol. 18. no. 3, pp. 10:1–10:21 (2016). https://doi.org/10.1145/2873069
4. Bonawitz, K., et al.: Practical secure aggregation for privacy-preserving machine learning. In: Thuraisingham, B.M., Evans, D., Malkin, T., Xu, D., (eds.) CCS 2017, pp. 1175–1191. ACM (2017). https://doi.org/10.1145/3133956.3133982
5. Dwork, C., Roth, A., et al.: The algorithmic foundations of differential privacy. Found. TrendstextRegistered Theor. Comput. Sci. 9(3-4), 211–407 (2014). https://doi.org/10.1561/0400000042
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