Evidence-Based Trust Mechanism Using Clustering Algorithms for Distributed Storage Systems
Giulia Traverso, Carlos Garcia Cordero, Mehrdad Nojoumian, Denise Demirel, Reza Azarderakhsh, Sheikh Mahbub Habib, Johannes A. Buchmann
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.
Privacy, Security and Trust 2017 (http://www.ucalgary.ca/pst2017/)
Place and Date
Calgary, Canada, August 28 - 30, 2017