基于动态冗余计算的大数据处理完整性保护

Zhimin Gao, Nicholas DeSalvo, P. D. Khoa, Seung-Hun Kim, Lei Xu, W. Ro, Rakesh M. Verma, W. Shi
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引用次数: 7

摘要

大数据是一个热门话题,在科学研究、财务分析和市场研究等不同领域都有不同的应用。云计算技术的发展为大数据应用提供了充分的平台。无论是公有的还是私有的,计算模型的外包和共享特性使得云中的大数据处理的安全性成为一个大问题。现有的工作大多注重对数据隐私的保护,而对处理过程的完整性保护关注较少,这可能导致大数据应用用户得出错误的结论,造成严重的后果。为了应对这一挑战,我们设计了一种基于信誉冗余计算的云环境下大数据处理完整性保护解决方案。实现和实验结果表明,该方案只增加了有限的成本,实现了完整性保护,具有实际应用价值。
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Integrity Protection for Big Data Processing with Dynamic Redundancy Computation
Big data is a hot topic and has found various applications in different areas such as scientific research, financial analysis, and market studies. The development of cloud computing technology provides an adequate platform for big data applications. No matter public or private, the outsourcing and sharing characteristics of the computation model make security a big concern for big data processing in the cloud. Most existing works focus on protection of data privacy but integrity protection of the processing procedure receives little attention, which may lead the big data application user to wrong conclusions and cause serious consequences. To address this challenge, we design an integrity protection solution for big data processing in cloud environments using reputation based redundancy computation. The implementation and experiment results show that the solution only adds limited cost to achieve integrity protection and is practical for real world applications.
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