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

Traverso, Giulia and Cordero, Carlos Garcia and Nojoumian, Mehrdad and Azarderakhsh, Reza and Demirel, Denise and Habib, Sheikh Mahbub and Buchmann, Johannes (2017):
Evidence-Based Trust Mechanism Using Clustering Algorithms for Distributed Storage Systems.
In: 15th Annual Conference on Privacy, Security and Trust (PST), Calgary, CA, 28.-30.8. 2017, [Online-Edition: https://www.ucalgary.ca/pst2017/],
[Conference or Workshop Item]

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 AS3, showing that this new evidence-based trust mechanism enhances the protection of the stored documents.

Item Type: Conference or Workshop Item
Erschienen: 2017
Creators: Traverso, Giulia and Cordero, Carlos Garcia and Nojoumian, Mehrdad and Azarderakhsh, Reza and Demirel, Denise and Habib, Sheikh Mahbub and Buchmann, Johannes
Title: Evidence-Based Trust Mechanism Using Clustering Algorithms for Distributed Storage Systems
Language: English
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 AS3, showing that this new evidence-based trust mechanism enhances the protection of the stored documents.

Title of Book: 15th Annual Conference on Privacy, Security and Trust (PST)
Uncontrolled Keywords: Solutions; S6; SPIN: Smart Protection in Infrastructures and Networks
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Theoretical Computer Science - Cryptography and Computer Algebra
20 Department of Computer Science > Telecooperation
DFG-Collaborative Research Centres (incl. Transregio)
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres
Profile Areas
Profile Areas > Cybersecurity (CYSEC)
LOEWE
LOEWE > LOEWE-Zentren
LOEWE > LOEWE-Zentren > CRISP - Center for Research in Security and Privacy
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1119: CROSSING – Cryptography-Based Security Solutions: Enabling Trust in New and Next Generation Computing Environments
Event Location: Calgary, CA
Event Dates: 28.-30.8. 2017
Date Deposited: 05 Sep 2017 10:35
Official URL: https://www.ucalgary.ca/pst2017/
Identification Number: TUD-CS-2017-0237
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