Paper 2017/728

Evidence-Based Trust Mechanism Using Clustering Algorithms for Distributed Storage Systems

Giulia Traverso, Carlos Garcia Cordero, Mehrdad Nojoumian, Reza Azarderakhsh, Denise Demirel, Sheikh Mahbub Habib, and Johannes Buchmann

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.

Metadata
Available format(s)
PDF
Category
Applications
Publication info
Published elsewhere. Major revision. 15th International Conference on Privacy, Security and Trust (PST2017)
Keywords
trust managementsocial secret sharingapplied cryptographydistributed storage systemscloud computingclustering algorithms
Contact author(s)
gtraverso @ cdc informatik tu-darmstadt de
History
2017-07-31: received
Short URL
https://ia.cr/2017/728
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2017/728,
      author = {Giulia Traverso and Carlos Garcia Cordero and Mehrdad Nojoumian and Reza Azarderakhsh and Denise Demirel and Sheikh Mahbub Habib and Johannes Buchmann},
      title = {Evidence-Based Trust Mechanism Using Clustering Algorithms for Distributed Storage Systems},
      howpublished = {Cryptology {ePrint} Archive, Paper 2017/728},
      year = {2017},
      url = {https://eprint.iacr.org/2017/728}
}
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