Multi-party Secure Privacy Computation Based on Secrecy Coding
Cong Hu, Ting Lei, Shuang Wang, Cuicui Zhang, Jiali Sun, Cuiling Liu, Peng Wang · 2022 5th World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM) · 2022
In this work, we propose a secrecy coding enabled multi-party secure privacy computation method, and the data of the multi participants can be used without harming the data privacy. By coding the secrecy data into secrecy vectors, the secrecy comparison between two parties can be converted to the partial scalar product problem of the secrecy vectors. Based on this design, we formulate the Millionaire and Relative Prime problems using the proposed secrecy coding. The security of the proposed method is guaranteed by selecting a random number locally at the multi users. Analysis shows that the proposed secrecy coding enabled multi-party secure privacy computation is lightweight and efficient.