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Distributed changing neighbors k-secure sum protocol for secure multiparty computation

机译:分布式更改邻居K-Secure Sum协议,用于安全多群计算

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Privacy preservation is an important area of the data mining because it allows the sharing of data between multiple parties. Various techniques are available to give privacy between multiple parties. In recent years, privacy preserving data mining has become more important because of the increasing ability to store personal data on the internet. In this paper, we discuss a novel protocol to compute the sum of an individual's data given by parties with zero leakage probability. We break the data blocks into segments and redistribute the segments among all the parties. After redistribution neighbors also changed their place. This is a scenario where it is impossible to know the private data of some other party.
机译:隐私保留是数据挖掘的重要领域,因为它允许在多方之间共享数据。可以提供各种技术在多方之间提供隐私。近年来,由于在互联网上存储个人数据的增加,隐私保留数据挖掘已经变得更加重要。在本文中,我们讨论了一种新颖的协议,用于计算零泄漏概率的各方给出的个人数据的总和。我们将数据块打破到段中,并重新分配各方之间的细分。再分配后,邻居也改变了他们的地方。这是一个方案,无法了解一些其他方的私人数据。

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