The present disclosure relates to a
data processing method, device, medium, equipment and product for secure computation. The secure computation is used for a first participant and a second participant to cooperatively compute the product of a target matrix and a target
column vector. The method comprises the following steps: encoding the target matrix into N polynomials; generating a second
ciphertext polynomial according to the N polynomials and a first
ciphertext polynomial sent by the second participant; generating an N-dimensional random
column vector, performing a masking process on the second
ciphertext polynomial by using the random
column vector, and sending the obtained masking polynomial after the masking process to the second participant; taking the random column vector as a second
shard of the product, and performing a target
data processing task based on the second
shard. In this way, the product of the matrix and the vector can be securely computed by using the properties of the operator ring, and the present scheme can be applied to the secure computation of the product of the matrix and the vector on the ring of any modulus. In addition, the
data security can be protected and the applicability can be improved in the model training scene by the present scheme.