Efficient security interface for high-performance Ceph storage systems

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 : 2024-10-23 DOI:10.1016/j.future.2024.107571
Fatemeh Khoda Parast , Seyed Alireza Damghani , Brett Kelly , Yang Wang , Kenneth B. Kent
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Abstract

Ceph portrays a resilient clustered storage solution with supporting object, block, and file storage capabilities with no single point of failure. Despite these qualifications, data confidentiality defines a concern in the system, as authentication and access control are the only data protection security services in Ceph. CephArmor was proposed as a third-party security interface to protect data confidentiality by adding an extra protection layer to data at rest. Despite the added layer, the initial design of the API needed to be more efficient in addressing security and performance simultaneously. In this study, we propose a new architectural design to address the associated issues with the preliminary prototype. Comprehensive performance and security analysis verify the improvement of the proposed method compared to the initial approach. The benchmark result has indicated a 37% improvement on average in IOPS, elapsed time, and bandwidth for the write benchmark compared to the initial model.
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高性能 Ceph 存储系统的高效安全接口
Ceph 是一种弹性集群存储解决方案,支持对象、块和文件存储功能,没有单点故障。尽管有这些优点,但数据保密性仍是系统中的一个问题,因为身份验证和访问控制是 Ceph 中唯一的数据保护安全服务。CephArmor 被提议作为第三方安全接口,通过为静态数据添加额外的保护层来保护数据的机密性。尽管增加了保护层,但最初设计的 API 需要更有效地同时解决安全性和性能问题。在本研究中,我们提出了一种新的架构设计,以解决与初步原型相关的问题。全面的性能和安全分析验证了与最初的方法相比,所提出的方法有所改进。基准结果表明,与初始模型相比,写入基准的 IOPS、耗时和带宽平均提高了 37%。
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来源期刊
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.
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