Yiqun Huang

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One crucial aspect of distributed data mining is privacy preserving. Secure multiparty computation (SMC) is a useful approach to solve privacy preserving in distributed data mining. When data is vertically partitioned, scalar product is a feasible tool to securely discover frequent itemsets of association rule mining. We first show that several of the(More)
Privacy preserving distributed data mining has become a promising research area. This paper addresses the problem of association rule mining where the global database is vertically partitioned. When transactions are distributed in different sites, scalar product is a feasible tool to discover frequent itemsets. We present a new protocol to compute scalar(More)
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