基于MapReduce的云存储数据审计方法研究

发布时间：2018-11-23 13:05

【摘要】：云存储是一种新兴的网络存储技术,它是云计算提供的一个重要服务。云存储因其快速、廉价和方便而广受云用户喜爱。然而,它也给云用户的外包数据带来了许多安全问题。其中一个重要问题就是如何确保半可信云服务器上数据的完整性。因此,云用户和云服务器亟需一个稳定、安全、可信的数据审计方法。随着大数据时代的到来,传统数据审计方案批量处理云环境下海量数据的效率不高;并且,随着移动客户端的流行,传统数据审计方案带给用户的在线负担太过繁重。因此,提出一种基于MapReduce编程框架的云数据审计方案,使用代理签名技术将用户对数据签名计算代理出去,并且并行化处理数据签名和批量审计过程。实验结果表明,所提方法明显提高了批量审计的效率,增强了云存储服务的可用性,并且减轻了用户的在线负担。
[Abstract]:Cloud storage is a new network storage technology, which is an important service provided by cloud computing. Cloud storage is popular with cloud users because it is fast, cheap and convenient. However, it also brings many security problems to the outsourced data of cloud users. One of the important issues is how to ensure the integrity of data on a semi-trusted cloud server. Therefore, cloud users and cloud servers need a stable, secure and trusted data audit method. With the arrival of big data era, the traditional data audit scheme is not efficient in batch processing of mass data in cloud environment; moreover, with the popularity of mobile clients, the online burden brought by traditional data audit scheme to users is too heavy. Therefore, a cloud data audit scheme based on MapReduce programming framework is proposed. The proxy signature technique is used to calculate the proxy to the data signature, and the process of data signature and batch audit is parallelized. Experimental results show that the proposed method can significantly improve the efficiency of batch audit, enhance the availability of cloud storage services, and reduce the online burden of users.
【作者单位】：武汉科技大学计算机科学与技术学院;湖北省智能信息处理与实时工业系统重点实验室;
【基金】：国家自然科学基金:云计算环境下基于行为的动态信任模型研究(61303117)资助
【分类号】：TP333

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