Application and Optimization Algorithms of Multi-Party Secure Computing in Information Communication

With the rapid growth of information technology (IT), the amount of data generated by various industries in modern society is exploding. However, while enjoying the convenience brought by data, how to ensure the privacy and security of data while maximizing its value has become a major challenge facing us. In this context, multi-party secure computing (SMPC) technology has emerged, providing strong technical support for data privacy protection. SMPC is a privacy computing technology based on cryptography, which can perform joint computation on multi-party data without leaking the original data, thereby ensuring the security and privacy of data. In order to further improve the efficiency and practicality of SMPC, this paper proposes an optimization algorithm and combines it with cloud computing. By adopting a distributed computing architecture, we can decompose and allocate computing tasks to multiple computing nodes, significantly improving computing efficiency. The experimental results show that our proposed SMPC optimization algorithm, when combined with cloud computing, not only significantly improves computational efficiency, but also demonstrates excellent performance in data privacy protection.