Biblio
Filters: Author is Araki, Shunsuke [Clear All Filters]
A Study on a DDH-Based Keyed Homomorphic Encryption Suitable to Machine Learning in the Cloud. 2022 IEEE International Conference on Consumer Electronics – Taiwan. :167—168.
.
2022. Homomorphic encryption is suitable for a machine learning in the cloud such as a privacy-preserving machine learning. However, ordinary homomorphic public key encryption has a problem that public key holders can generate ciphertexts and anyone can execute homomorphic operations. In this paper, we will propose a solution based on the Keyed Homomorphic-Public Key Encryption proposed by Emura et al.