云存储数据完整性检测技术研究

发布时间：2018-08-20 17:15

【摘要】：云计算已经成为近年来研究热点,成为当前信息技术发展的趋势。它提供一系列服务供用户使用,云存储作为一种服务形式随之产生。云计算有着传统模式无法拥有的优势：提供方便的计算资源共享池、资源灵活、安全可控、数据可靠、节约成本、统一管理、廉价的容错性,所以云服务相关产品越来越受到用户的追捧。云存储作为云服务的核心服务模块,更是以其高扩展性、高可靠性、低成本、方便的数据管理和方便的访问以及安全可靠的数据管理得到用户青睐。云存储中主要的数据管理模式是用户将数据转移到云端,随之而来的是对数据安全的挑战。本文主要是对云存储安全中的数据完整性检测技术的研究,首先分析云存储平台的特性,之后分析云安全领域所面临的挑战,对现有的完整性检测的技术进行研究,学习研究完整性检测的模型,分析相关模型的优缺点。借鉴经典的完整性检测的研究思路,设计出一种符合云存储数据完整性检测的模型。本文设计的方案主要是基于数据持有证明检测模型设计的方案,同时为了满足云存储的特性设计一种第三方完整性检测的系统模型,提出批量数据持有检测(Batch Dynamic Provable Data Possession, BDPDP)方案,该方案的设计可以满足高效可靠地完成完整性检测。为了满足云存储完整性检测方案的需求,本文提出一种嵌入式哈希树结构Embedded Merkle Hash Tree (EMHT)。该结构是基于双线性聚合短签名算法进行完整性验证,能够进行批量完整性验证工作。之后对本模型进行安全分析,通过实验与经典算法进行对比完整性验证的存储开销定位性能,根据实验结果分析本文方案的优缺点,最后对本文提出方案进行总结和展望。本文提出的研究算法在云存储数据完整性验证中有较低的计算开销和通信开销,保证完整性验证的效率,同时还可以在后续批量结构中对错误数据进行快速定位工作。本文分析该设计方案对云存储动态性有很好的支持,本文提出的算法为云存储数据完整性验证提供一个很好地研究方向。
[Abstract]:Cloud computing has become a research hotspot in recent years, and has become the trend of the development of information technology. It provides a range of services for users to use, cloud storage as a form of service followed. Cloud computing has the advantages that the traditional model can not have: provide a convenient pool of computing resources, flexible resources, security and controllable, reliable data, cost savings, unified management, cheap fault tolerance, So cloud service related products are more and more popular with users. Cloud storage, as the core service module of cloud service, is favored by users for its high scalability, high reliability, low cost, convenient data management and convenient access as well as secure and reliable data management. The main data management mode in cloud storage is that users move data to the cloud, which brings challenges to data security. In this paper, the data integrity detection technology in cloud storage security is studied. Firstly, the characteristics of cloud storage platform are analyzed, then the challenges in cloud security field are analyzed, and the existing integrity detection technology is studied. Learning to study the integrity of the model, analysis of the advantages and disadvantages of the relevant models. A model for integrity detection of cloud storage data is designed based on the classical research ideas of integrity detection. In order to satisfy the characteristics of cloud storage, a third-party integrity detection system model is designed, and a batch data holding detection (Batch Dynamic Provable Data Possession, BDPDP) scheme is proposed. The design of this scheme can meet the requirement of high efficiency and reliability. In order to meet the requirements of cloud storage integrity detection scheme, an embedded hash tree structure Embedded Merkle Hash Tree (EMHT). Is proposed in this paper. The structure is based on bilinear aggregate short signature algorithm for integrity verification and batch integrity verification. Then the security of the model is analyzed, and the storage cost localization performance is compared with the classical algorithm. According to the experimental results, the advantages and disadvantages of the proposed scheme are analyzed. Finally, the proposed scheme is summarized and prospected. The algorithm proposed in this paper has low computational and communication overhead in cloud storage data integrity verification, which ensures the efficiency of integrity verification, and can also be used to locate error data quickly in subsequent batch structures. This paper analyzes that the design scheme has a good support for cloud storage dynamics, and the algorithm proposed in this paper provides a good research direction for cloud storage data integrity verification.
【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP333;TP309

【共引文献】