Computing the Ratio of Secure Summations (RSS) is one of the most important tools for privacy preserving distributed data mining. It refers to such a problem: given n parties and theirrespective secret values (xi,yi), where i = 1; : : : ; n, how can they get the value ofPni=1 xi=Pni=1 yiwithout disclosing (xi,yi),Pni=1 xi andPni=1 yi? In this paper, we propose a new method to solve this problem. Compared with existing methods, our method is not only secure under the assumption of semi honest,but also can resist collusion attacks—even when all but one party are corrupt. At the same time, the computational complexity and communication complexity of our method are both O(n). Therefore, it can meet the needs of practical application in terms of both security and efficiency. In addition to the theoretical guarantee, the practical usability of our method is also verified through experiments by constructing Naive Bayes classifiers in a privacy preserving distributed environment
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