Method and electronic device for performing convolutional neural network operations on batch of input images using homomorphic encryption

Abstract

Provided are a method and an electronic device for performing convolutional neural network operations on a batch of input images using homomorphic encryption. The method includes: for each channel of the batch of the input images, grouping pixel values at the same location in the images included in the batch into a single vector, and encrypting the grouped vectors using a homomorphic encryption method to obtain a first ciphertext; for each channel and each coefficient of the ciphertext, grouping coefficients of the first ciphertext corresponding to all pixel locations to generate polynomials, and configuring the polynomials into a single matrix; multiplying the matrix by a polynomial matrix representing a convolution filter to obtain a result matrix, and performing a modulo operation on each element of the result matrix to generate an encrypted convolution operation result, the operation being performed on unencrypted matrices; and rearranging polynomial coefficients of the result matrix to generate a second ciphertext for the batch of the images after the convolution layer is applied, in which the second ciphertext is encrypted by the same homomorphic encryption method as the first ciphertext.

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