• 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 >A Privacy Leakage Upper Bound Constraint-Based Approach for Cost-Effective Privacy Preserving of Intermediate Data Sets in Cloud
【24h】

A Privacy Leakage Upper Bound Constraint-Based Approach for Cost-Effective Privacy Preserving of Intermediate Data Sets in Cloud

机译：基于隐私泄漏上限约束的成本有效的云中中间数据集隐私保护方法

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

Cloud computing provides massive computation power and storage capacity which enable users to deploy computation and data-intensive applications without infrastructure investment. Along the processing of such applications, a large volume of intermediate data sets will be generated, and often stored to save the cost of recomputing them. However, preserving the privacy of intermediate data sets becomes a challenging problem because adversaries may recover privacy-sensitive information by analyzing multiple intermediate data sets. Encrypting ALL data sets in cloud is widely adopted in existing approaches to address this challenge. But we argue that encrypting all intermediate data sets are neither efficient nor cost-effective because it is very time consuming and costly for data-intensive applications to en/decrypt data sets frequently while performing any operation on them. In this paper, we propose a novel upper bound privacy leakage constraint-based approach to identify which intermediate data sets need to be encrypted and which do not, so that privacy-preserving cost can be saved while the privacy requirements of data holders can still be satisfied. Evaluation results demonstrate that the privacy-preserving cost of intermediate data sets can be significantly reduced with our approach over existing ones where all data sets are encrypted.
机译：云计算提供了巨大的计算能力和存储容量，使用户无需基础设施投资即可部署计算和数据密集型应用程序。随着此类应用程序的处理，将生成大量中间数据集，并经常存储这些中间数据集以节省重新计算它们的成本。但是，保留中间数据集的隐私成为一个具有挑战性的问题，因为对手可能会通过分析多个中间数据集来恢复对隐私敏感的信息。现有方法广泛采用了对云中的所有数据集进行加密的方法来应对这一挑战。但是我们认为对所有中间数据集进行加密既不高效也不具有成本效益，因为数据密集型应用程序在对其执行任何操作时频繁地对数据集进行加密/解密非常耗时且昂贵。在本文中，我们提出了一种基于上限隐私泄漏约束的新颖方法，该方法可识别哪些中间数据集需要加密而哪些不需要，从而可以节省隐私保护成本，同时仍然可以满足数据持有者的隐私要求。满意。评估结果表明，与所有数据集都经过加密的现有数据集相比，我们的方法可以大大降低中间数据集的隐私保护成本。

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