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Integrating Multi-Modal Cloud Features within a Multi-Dimensional Encryption Space

Ye, Bin and Howells, Gareth (2016) Integrating Multi-Modal Cloud Features within a Multi-Dimensional Encryption Space. In: 2015 Sixth International Conference on Emerging Security Technologies (EST). IEEE. E-ISBN 978-1-4673-9799-5. (doi:10.1109/EST.2015.12) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1109/EST.2015.12

Abstract

The problem of combining multi-modal features which extract from characteristics of given Cloud Computing Servers in the pattern recognition system is well known difficult. This paper addresses a novel efficient technique for normalizing sets of features which are highly multi-modal in nature, so as to allow them to be incorporated from a multi-dimensional feature distribution space. The intend system identify the modes of each distribution and for removing any possible correlation between the feature data to allow to be used in an encryption key generation system.

Item Type: Book section
DOI/Identification number: 10.1109/EST.2015.12
Uncontrolled keywords: servers; kernel; encryption; cloud computing; feature extraction; linux; hardware
Subjects: T Technology
Divisions: Faculties > Sciences > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: Tina Thompson
Date Deposited: 01 Sep 2015 08:50 UTC
Last Modified: 25 Sep 2019 10:50 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/50340 (The current URI for this page, for reference purposes)
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