Securing Manufacturing Business Intelligence for the Industrial Internet of Things

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Widespread interest in the emerging area of predictive analytics is driving the manufacturing industry to explore new approaches
to the collection and management of data through Industrial Internet of Things (IIoT) devices. Analytics processing for Business Intelligence (BI) is an intensive task, presenting both a competitive advantage as well as a security vulnerability in terms of the potential for losing Intellectual Property (IP). This article explores two approaches to securing BI in the manufacturing domain. Simulation results indicate that a Unified Threat Management (UTM) model is simpler to maintain and has less potential vulnerabilities than a distributed security model. Conversely,
a distributed model of security out-performs the UTM model and offers more scope for the use of existing hardware resources. In conclusion, a hybrid security model is proposed where security controls are segregated into a multi-cloud architecture.
LanguageEnglish
Title of host publicationFourth International Congress on Information and Communication Technology
PublisherSpringer Verlag
Number of pages16
Publication statusAccepted/In press - 22 Jan 2019
EventFourth International Congress on Information and Communication Technology - London, United Kingdom
Duration: 25 Feb 201926 Feb 2019
http://www.icict.co.uk/

Conference

ConferenceFourth International Congress on Information and Communication Technology
Abbreviated titleICICT 2019
CountryUnited Kingdom
CityLondon
Period25/02/1926/02/19
Internet address

Fingerprint

Competitive intelligence
Intellectual property
Internet of things
Hardware
Processing
Industry

Cite this

Hill, G., Al-Aqrabi, H., Lane, P., & Aagela, H. (Accepted/In press). Securing Manufacturing Business Intelligence for the Industrial Internet of Things. In Fourth International Congress on Information and Communication Technology [174] Springer Verlag.
Hill, Graham ; Al-Aqrabi, Hussain ; Lane, Philip ; Aagela, Hamza. / Securing Manufacturing Business Intelligence for the Industrial Internet of Things. Fourth International Congress on Information and Communication Technology. Springer Verlag, 2019.
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abstract = "Widespread interest in the emerging area of predictive analytics is driving the manufacturing industry to explore new approachesto the collection and management of data through Industrial Internet of Things (IIoT) devices. Analytics processing for Business Intelligence (BI) is an intensive task, presenting both a competitive advantage as well as a security vulnerability in terms of the potential for losing Intellectual Property (IP). This article explores two approaches to securing BI in the manufacturing domain. Simulation results indicate that a Unified Threat Management (UTM) model is simpler to maintain and has less potential vulnerabilities than a distributed security model. Conversely,a distributed model of security out-performs the UTM model and offers more scope for the use of existing hardware resources. In conclusion, a hybrid security model is proposed where security controls are segregated into a multi-cloud architecture.",
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author = "Graham Hill and Hussain Al-Aqrabi and Philip Lane and Hamza Aagela",
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Hill, G, Al-Aqrabi, H, Lane, P & Aagela, H 2019, Securing Manufacturing Business Intelligence for the Industrial Internet of Things. in Fourth International Congress on Information and Communication Technology., 174, Springer Verlag, Fourth International Congress on Information and Communication Technology, London, United Kingdom, 25/02/19.

Securing Manufacturing Business Intelligence for the Industrial Internet of Things. / Hill, Graham; Al-Aqrabi, Hussain; Lane, Philip; Aagela, Hamza.

Fourth International Congress on Information and Communication Technology. Springer Verlag, 2019. 174.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - Widespread interest in the emerging area of predictive analytics is driving the manufacturing industry to explore new approachesto the collection and management of data through Industrial Internet of Things (IIoT) devices. Analytics processing for Business Intelligence (BI) is an intensive task, presenting both a competitive advantage as well as a security vulnerability in terms of the potential for losing Intellectual Property (IP). This article explores two approaches to securing BI in the manufacturing domain. Simulation results indicate that a Unified Threat Management (UTM) model is simpler to maintain and has less potential vulnerabilities than a distributed security model. Conversely,a distributed model of security out-performs the UTM model and offers more scope for the use of existing hardware resources. In conclusion, a hybrid security model is proposed where security controls are segregated into a multi-cloud architecture.

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Hill G, Al-Aqrabi H, Lane P, Aagela H. Securing Manufacturing Business Intelligence for the Industrial Internet of Things. In Fourth International Congress on Information and Communication Technology. Springer Verlag. 2019. 174