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With the rapid development of the automotive industry, research on the internet of vehicles (IoV) has become a hot topic in the field of automobiles. Considering the privacy of data collected from vehicles, this paper proposes a novel multiparty homomorphic encryption scheme (MHE) for secure multiparty computation without the need for a trusted third party. The scheme ensures efficient computation of data while preserving the privacy of each party’s data. It consists of four phases: construction, computation, recombination, and refreshing. In the recombination phase, the key is reconstructed using a span program, enabling secure computation among participating parties under a semi-honest model. Finally, we compare the proposed scheme with mainstream approaches and conduct experiments within the framework of federated learning. Through both experimental and theoretical analyses, the performance of the proposed scheme is comprehensively evaluated, demonstrating its efficiency and correctness.
Mi et al. (Fri,) studied this question.