Research Of Secure Multipapty Computation Protocols

With the continuous development of network technology, and with the appearance of high quality computers and net grid, the meanings and mode of computations are mostly changed. Users can make use of the powerful computation resources to complete their computation tasks. Therefore in this environment, the safety of users'data become very important and necessary.Secure Multi-party Computation (SMC) is a computation among a set of participants who do not have confidence in one another, in which participants collaborate on desired tasks but do not reveal private information of their own. Since it was initially suggested by A.C.Yao in the 1980s, SMC have been a major part of modern cryptography and attracted numerous researchers'interest. It's the basis of many distributed cryptographic protocols such as threshold cryptosystem, electronic voting and electronic auction, etc. Secure multi-party computation has extended the traditional distributed computation and information security areas. A new computation mode was created for network collaborative computation. It is very significant to solve the information security problems in the network environment.Researches on the SMC are very complicated tasks. And researches on the special issues are far from ideal. In this paper, secure two-party and multiparty computation protocol problems were discussed which including polynomial evaluation and multiplication, elementary function operation (except inverse trigonometric function), determinant evalua-tion, vector and matrix related operation, solving linear equation and so on. Some existing secure two-party computation protocols of semi-honest models were generalized. A series of secure multiparty computation protocols were advanced. Correctness, security and complexi-ty of these protocols were discussed. In addition, it was discussed the secure two-party and multiparty computations of malicious models. Some foundations and extended protocols were advanced which can be tolerated under the malicious behavior models.