On Enhancing Security for Division Homomorphism with ElGamal
DOI:
https://doi.org/10.32473/flairs.36.133266Keywords:
ML, machine learning, AI, Artificial Intelligence, homomorphism, Full homomorphism, Division, cryptosystem, homomorphic cryptography, Elgamal, HomomorphismAbstract
Secure auctions and machine learning in cloud increasingly employs multi-party and homomorphic encryption support.
A modification to Elgamal public key cryptosystem was shown to enable homomorphic division using an encoding of plaintext as fractions with numerator and denominator encrypted separately. However we notice that unlike for other homomorphic cryptography schemes, the obtained division homomorphism allows for the retrieval of the input secrets from the result of the division. Since this cancels the benefit of the encryption, we propose the introduction of a masking operation based on random factors and discuss its success with operations in Zp and Q.
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Copyright (c) 2023 Marius Silaghi, Ameerah Alsulami

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.