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Deploying Visual Analytics Through a Multi-cloud Service Store with Encrypted Big Data (Short Paper)

Shackleton, Mark B., El-Moussa, Fadi, Rowlingson, Robert, Healing, Alex, Crowther, John, Daniel, Joshua, Dimitrakos, Theo, Sajjad, Ali (2016) Deploying Visual Analytics Through a Multi-cloud Service Store with Encrypted Big Data (Short Paper). In: Debruyne, Christophe and Panetto, Hervé and Meersman, Robert and Dillon, Tharam and Kühn, Eva and O'Sullivan, Declan and Ardagna, Claudio Agostino, eds. Lecture Notes in Computer Science. On the Move to Meaningful Internet Systems: OTM 2016 Conferences. Lecture Notes in Computer Science (LNCS) , 10033. pp. 883-889. Springer ISBN 978-3-319-48471-6. E-ISBN 978-3-319-48472-3. (doi:10.1007/978-3-319-48472-3_55) (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) (KAR id:58309)

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/10.1007/978-3-319-48472-3_55

Abstract

The benefits of Cloud Computing are now widely recognised, in terms of easy, flexible, scalable and cost effective deployment of services and storage. At the same time, the growth in Big Data solutions is offering a plethora of new service opportunities. However, significant barriers of trust and privacy concerns are slowing the adoption of Big Data cloud services.

In this paper we describe how a Visual Analytics system can be flexibly deployed via a multi-cloud application store. The supporting infrastructure (IaaS) is protected via innovative security protection capabilities, while associated Big Data resources can be protected via encryption and access control.

The novel Visual Analytics capability makes analysis of Big Data in the cloud easier and faster, thereby empowering data analysts with attractive new tools, while the security features help to tackle issues of privacy and trust for big data cloud deployments

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1007/978-3-319-48472-3_55
Uncontrolled keywords: Visual analytics, Cyber security, Encryption, Trust, Big data, Cloud, Service store
Divisions: Faculties > Sciences > School of Computing
Depositing User: Theodosios Dimitrakos
Date Deposited: 03 Apr 2017 09:25 UTC
Last Modified: 29 May 2019 18:06 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/58309 (The current URI for this page, for reference purposes)
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