Reference : Efficient AGCD-Based Homomorphic Encryption for Matrix and Vector Arithmetic
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
Computational Sciences
Efficient AGCD-Based Homomorphic Encryption for Matrix and Vector Arithmetic
Lima Pereira, Hilder Vitor mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) >]
Applied Cryptography and Network Security
Springer International Publishing
18th International Conference on Applied Cryptography and Network Security Search within this conference
from 19-10-2020 to 2210-2020
[en] Homomorphic encryption ; AGCD ; Nondeterministic finite automata ; Naïve Bayes Classifier
[en] We propose a leveled homomorphic encryption scheme based on the Approximate Greatest Common Divisor (AGCD) problem that operates natively on vectors and matrices. To overcome the limitation of large ciphertext expansion that is typical in AGCD-based schemes, we randomize the ciphertexts with a hidden matrix, which allows us to choose smaller parameters. To be able to efficiently evaluate circuits with large multiplicative depth, we use a decomposition technique à la GSW. The running times and ciphertext sizes are practical: for instance, for 100 bits of security, we can perform a sequence of 128 homomorphic products between 128-dimensional vectors and 128×128 matrices in less than one second. We show how to use our scheme to homomorphically evaluate nondeterministic finite automata and also a Naïve Bayes Classifier.

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