DSDM-TCSE: Deterministic storage and deletion mechanism for trusted cloud service environments

IF 6.2 2区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS

Future Generation Computer Systems-The International Journal of Escience Pub Date : 2024-11-19 DOI:10.1016/j.future.2024.107611

Wenlong Yi, Chuang Wang, Jie Chen, Sergey Kuzmin, Igor Gerasimov, Xiangping Cheng

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引用次数: 0

Abstract

The separation of data ownership and management rights in cloud storage architectures results in losing control over outsourced data, making it challenging to achieve deterministic deletion and verify-deletion results. This predicament precipitates security vulnerabilities that impede the advancement of cloud services. This study proposes a deterministic storage and deletion mechanism for trusted cloud service environments (DSDM-TCSEs). This mechanism establishes a three-layer cloud data interaction framework, adopting blockchain as the communication intermediary layer, and employs techniques such as overwrite key negotiation strategy and CP-ABE encryption to achieve fine-grained storage, deletion control, and deletion result verification of cloud data, effectively isolating the cloud service provider and protecting data privacy. It also proposes an efficient evidence strategy based on a cuckoo filter and data noise vectors for rapid construction and verification. Experimental results show that this method improves the speed of evidence construction and verification by 83% compared to related schemes and saves 5% storage overhead when the number of attributes is large, demonstrating good time and space performance and providing a solid guarantee for achieving deterministic storage and deletion in trusted cloud services.

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DSDM-TCSE：可信云服务环境的确定性存储和删除机制

在云存储架构中，数据所有权和管理权的分离导致对外包数据失去控制，使实现确定性删除和验证删除结果具有挑战性。这种困境造成了安全漏洞，阻碍了云服务的发展。本研究提出了可信云服务环境（DSDM-TCSE）的确定性存储和删除机制。该机制建立了三层云数据交互框架，采用区块链作为通信中介层，采用覆盖密钥协商策略和CP-ABE加密等技术，实现了云数据的细粒度存储、删除控制和删除结果验证，有效隔离了云服务提供商，保护了数据隐私。同时，它还提出了一种基于布谷鸟滤波器和数据噪声矢量的高效证据策略，以实现快速构建和验证。实验结果表明，与相关方案相比，该方法的证据构建和验证速度提高了83%，当属性数量较多时，可节省5%的存储开销，表现出良好的时间和空间性能，为在可信云服务中实现确定性存储和删除提供了坚实的保障。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Future Generation Computer Systems-The International Journal of Escience 工程技术-计算机：理论方法

CiteScore

19.90

自引率

2.70%

发文量

376

审稿时长

10.6 months

期刊介绍： Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.