• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >Privacy-Preserving Multiparty Collaborative Mining with Geometric Data Perturbation
【24h】

Privacy-Preserving Multiparty Collaborative Mining with Geometric Data Perturbation

机译：具有几何数据扰动的隐私保护多方协作挖掘

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In multiparty collaborative data mining, participants contribute their own data sets and hope to collaboratively mine a comprehensive model based on the pooled data set. How to efficiently mine a quality model without breaching each party's privacy is the major challenge. In this paper, we propose an approach based on geometric data perturbation and data mining service-oriented framework. The key problem of applying geometric data perturbation in multiparty collaborative mining is to securely unify multiple geometric perturbations that are preferred by different parties, respectively. We have developed three protocols for perturbation unification. Our approach has three unique features compared to the existing approaches: 1) with geometric data perturbation, these protocols can work for many existing popular data mining algorithms, while most of other approaches are only designed for a particular mining algorithm; 2) both the two major factors: data utility and privacy guarantee are well preserved, compared to other perturbation-based approaches; and 3) two of the three proposed protocols also have great scalability in terms of the number of participants, while many existing cryptographic approaches consider only two or a few more participants. We also study different features of the three protocols and show the advantages of different protocols in experiments.
机译：在多方协作数据挖掘中，参与者贡献自己的数据集，并希望基于池化数据集协作地挖掘一个综合模型。如何有效挖掘质量模型而又不破坏各方隐私是主要的挑战。在本文中，我们提出了一种基于几何数据扰动和面向数据挖掘的面向服务框架的方法。在多方协作挖掘中应用几何数据扰动的关键问题是安全地统一分别由不同方偏爱的多个几何扰动。我们已经开发了三种用于扰动统一的协议。与现有方法相比，我们的方法具有三个独特的功能：1）具有几何数据扰动，这些协议可用于许多现有的流行数据挖掘算法，而其他大多数方法仅适用于特定的挖掘算法； 2）两个主要因素：与其他基于扰动的方法相比，数据实用性和隐私保证得到了很好的保护；和3）三种协议中的两种在参与者数量方面也具有很大的可扩展性，而许多现有的加密方法仅考虑两个或几个更多的参与者。我们还研究了这三种协议的不同功能，并在实验中展示了不同协议的优势。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号