Privacy-Preserving Classification of Customer Data without Loss of Accuracy
Author:
Publisher
Society for Industrial and Applied Mathematics
Link
https://epubs.siam.org/doi/pdf/10.1137/1.9781611972757.9
Cited by 68 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Fully Homomorphic Privacy-Preserving Naive Bayes Machine Learning and Classification;Proceedings of the 11th Workshop on Encrypted Computing & Applied Homomorphic Cryptography;2023-11-26
2. Application of Computer Simulation to the Anonymization of Personal Data: State-of-the-Art and Key Points;Programming and Computer Software;2023-07-28
3. APPLICATION OF COMPUTER SIMULATION TO THE ANONYMIZATION OF PERSONAL DATA: STATE-OF-THE-ART AND KEY POINTS;Программирование;2023-07-01
4. A novel cryptographic protocol for privacy preserving classification over distributed encrypted databases;Journal of Banking and Financial Technology;2022-05-25
5. Hierarchical Identity Based Inner Product Functional Encryption for Privacy Preserving Statistical Analysis Without q-type Assumption;Communications in Computer and Information Science;2022
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