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Multi-dimensional key generation of ICMetrics for cloud computing

Ye, Bin, Howells, Gareth, Haciosman, Mustafa, Wang, Frank Z. (2015) Multi-dimensional key generation of ICMetrics for cloud computing. Journal of Cloud Computing, 4 (1). ISSN 2192-113X. (doi:10.1186/s13677-015-0044-6)

Abstract

Despite the rapid expansion and uptake of cloud based services, lack of trust in the provenance of such services represents a significant inhibiting factor in the further expansion of such service. This paper explores an approach to assure trust and provenance in cloud based services via the generation of digital signatures using properties or features derived from their own construction and software behaviour. The resulting system removes the need for a server to store a private key in a typical Public/Private-Key Infrastructure for data sources. Rather, keys are generated at run-time by features obtained as service execution proceeds. In this paper we investigate several potential software features for suitability during the employment of a cloud service identification system. The generation of stable and unique digital identity from features in Cloud computing is challenging because of the unstable operation environments that implies the features employed are likely to vary under normal operating conditions. To address this, we introduce a multi-dimensional key generation technology which maps from multi-dimensional feature space directly to a key space. Subsequently, a smooth entropy algorithm is developed to evaluate the entropy of key space.

Item Type: Article
DOI/Identification number: 10.1186/s13677-015-0044-6
Uncontrolled keywords: Cryptography; Cloud computing; Security; Key generation; ICMetrics; Multi-dimensional space
Subjects: T Technology
Divisions: Faculties > Sciences > School of Engineering and Digital Arts
Faculties > Sciences > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: Tina Thompson
Date Deposited: 18 Nov 2015 10:37 UTC
Last Modified: 29 May 2019 16:25 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/52016 (The current URI for this page, for reference purposes)
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