Evidence-Based Trust Mechanism Using Clustering Algorithms for Distributed Storage Systems (Short Paper)

Giulia Traverso, Carlos Garcia Cordero, Mehrdad Nojoumian, R. Azarderakhsh, Denise Demirel, Sheikh Mahbub Habib, J. Buchmann
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引用次数: 6

Abstract

In distributed storage systems, documents are shared among multiple Cloud providers and stored within their respective storage servers. In social secret sharing-based distributed storage systems, shares of the documents are allocated according to the trustworthiness of the storage servers. This paper proposes a trust mechanism using machine learning techniques to compute evidence-based trust values. Our mechanism mitigates the effect of colluding storage servers. More precisely, it becomes possible to detect unreliable evidence and establish countermeasures in order to discourage the collusion of storage servers. Furthermore, this trust mechanism is applied to the social secret sharing protocol AS^3, showing that this new evidence-based trust mechanism enhances the protection of the stored documents.
基于聚类算法的分布式存储系统基于证据的信任机制(短论文)
在分布式存储系统中,文档在多个云提供商之间共享,并存储在各自的存储服务器中。在基于社会秘密共享的分布式存储系统中,文档的共享是根据存储服务器的可信度来分配的。本文提出了一种利用机器学习技术计算基于证据的信任值的信任机制。我们的机制减轻了串通存储服务器的影响。更准确地说,它可以发现不可靠的证据,并建立对策,以阻止存储服务器的勾结。并将该信任机制应用于社会秘密共享协议AS^3中,结果表明,该基于证据的信任机制增强了对存储文档的保护。
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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