Faster Private Decision Tree Evaluation for Batched Input from Homomorphic Encryption
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-71073-5_1
Reference34 articles.
1. Azogagh, S., Delfour, V., Gambs, S., Killijian, M.: PROBONITE: private one-branch-only non-interactive decision tree evaluation. In: Brenner, M., Costache, A., Rohloff, K. (eds.) Proceedings of the 10th Workshop on Encrypted Computing & Applied Homomorphic Cryptography, Los Angeles, CA, USA, 7 November 2022, pp. 23–33. ACM (2022). https://doi.org/10.1145/3560827.3563377
2. Bai, J., Song, X., Cui, S., Chang, E.C., Russello, G.: Scalable private decision tree evaluation with sublinear communication. In: Suga, Y., Sakurai, K., Ding, X., Sako, K. (eds.) ASIACCS 2022, pp. 843–857. ACM Press (2022). https://doi.org/10.1145/3488932.3517413
3. LNCS;C Bonte,2022
4. Bost, R., Popa, R.A., Tu, S., Goldwasser, S.: Machine learning classification over encrypted data. In: NDSS 2015. The Internet Society (2015). https://doi.org/10.14722/ndss.2015.23241
5. Lecture Notes in Computer Science;Z Brakerski,2012
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