Zero-knowledge proof (ZKP) techniques further bolster the privacy and security of SMPC by allowing one party to prove the correctness of a statement without divulging any information beyond the veracity of the claim.

In this article, we have thoroughly examined the intricate interplay between zero-knowledge proofs and machine learning, emphasizing the significance of privacy-preserving computation while maintaining the accuracy and utility of the models.