The Study Of E-commerce Privacy Protection Collaborative Computing Based On Secure Multi-party Protocol

The progress of information technology to promote the informationization of collaborative computing constantly moving forward, Participants can do some calculation of complex function by the "communication" in the network environment information.However, all involved in the calculation of the participants generally belong to personal private information or data, the problem of privacy protection becomes an important restriction factor for the development of collaborative computing.The participants contribute their own private data,and protect their private information is not leaked to other participants which has become the research goal for many researchers.In1982, A.C.Yao gave the concept of secure multi-party computation first,the theory and method have attracted many researchers’ attention,the inheritance and development of a large amount of secure multi-party computation theory and application research.Secure multi-party computation is an important branch of modern cryptography research and research field in information security.The main idea is following:in a distributed network, two or more parties carry out an algorithm that makes it possible to get the correct output in the parties according to their own secret input and implement at the same time it can protect their input information of privacy.Collaborative filtering has become a major tool of personalized recommendation system.However, the sparseness problem of data in collaborative filtering has affected the effect of the recommendation.Currently, more and more e-commerce sites looking for the same type of cooperation between sites.Based on the above problems,this paper’s work mainly include several aspects as following:1) Discourses the current development situation of the recommendation algorithm, the classic recommendation algorithms and the algorithms for privacy protection;2) On the basis of the traditional user ratings for collaborative filtering recommendation algorithm makes some improving;3) Focus on secure multi-party computation protocol, lists basic protocol and application of secure multi-party computation, designs a set of collaborative filtering recommendation algorithm based on secure multi-party computation and analyzes the security and validity; 4) Design a secure protocol to solve the problem of the total sales in business decisions, make a example verification,and analysis the correctness of the scheme, the security and complexity.