Secure Multiparty Computation of Statistical Distribution

Secure multi-party computation is now a crucial privacy preserving technology in network computing environment, and it plays an important role in cryptography. It is a basic block to construct other cryptographic protocol, and is recently a research focus in international cryptographic community. The researchers from home and abroad have made extensive researches on secure multi-party computations, and a lot of theoretical and practical achievements have been obtained, and yet a lot of practical problems need to be further studied. The authors first briefly introduce the state of the art in the study of secure multi-party computation, and some problems need to be further studied. Secondly, they study the secure problems that are encountered in statistics. Aiming at privacy preserving computing of statistical distribution, which is frequently encountered in statistics, and based on the intractability of computing discrete logarithm and using rigorous logic, three solutions are proposed to this problem. The privacy preserving property of these solutions are proved by simulation paradigm. The study of this problem has not been read in the literature. These solutions are of great importance in practical privacy preserving statistical computation. They can be used to protect the privacy of the informant, so that the informant need not worry about the leakage of their privacy. This makes the statistical results be more reliable and have more reference value.