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- W1605515141 abstract "Recently, privacy issues have becomes important in data mining, especially when data is horizontally or vertically partitioned. For the vertically partitioned case, many data mining problems can be reduced to securely computing the scalar product. Among these problems, we can mention association rule mining over vertically partitioned data. Efficiency of a secure scalar product can be measured by the overhead of communication needed to ensure this security. Several solutions have been proposed for privacy preserving association rule mining in vertically partitioned data. But the main drawback of these solutions is the excessive overhead communication needed for ensuring data privacy. In this paper we propose a new secure scalar product with the aim to reduce the overhead communication." @default.
- W1605515141 created "2016-06-24" @default.
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- W1605515141 date "2009-01-01" @default.
- W1605515141 modified "2023-09-26" @default.
- W1605515141 title "A Secure Protocol to Maintain Data Privacy in Data Mining" @default.
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- W1605515141 doi "https://doi.org/10.1007/978-3-642-03348-3_40" @default.
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