期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2011
卷号：8
期号：4
出版社：IJCSI Press
摘要：Use of technology for data collection and analysis has seen an unprecedented growth in the last couple of decades. Individuals and organizations generate huge amount of data through everyday activities. This data is either centralized for pattern identification or mined in a distributed fashion for efficient knowledge discovery and collaborative computation. This has raised serious concerns about privacy issues. The data mining community has responded to this challenge by developing a new breed of algorithms that are privacy preserving. The main objective of data mining is to extract the identified pattern for efficient knowledge discovery with centralized or decentralized collaborative computation. This paper focuses on developing secure computational model for preserving the privacy of the distributed data by performing multiparty computation in peer-to-peer network. However this approach requires that participating parties are attached to the coordinator of the peer-to-peer network through a specified path and maintain privacy by performing certain application specific computation on their local site. The computation is performed by taking the distributed data-set of a particular scenario through centralized and decentralized fashion.
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