A Secure Cloud Migration, Monitoring and Analytics Framework for Industrial Internet of Things

Rafiullah Khan; Kieran McLaughlin; BooJoong Kang; David Laverty; Sakir Sezer

doi:10.1109/WF-IoT48130.2020.9221106

A Secure Cloud Migration, Monitoring and Analytics Framework for Industrial Internet of Things

Rafiullah Khan, Kieran McLaughlin, BooJoong Kang, David Laverty, Sakir Sezer

School of Electronics, Electrical Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

The fourth industrial revolution combines cutting-edge technologies such as Industrial Internet of Things (IIoT) and cloud computing. However, this inevitable revolution faces challenges due to the presence of legacy equipment in industrial systems. Legacy equipment hinders the adoption of emerging cloud technologies due to data privacy, security and interoperability issues. This paper proposes a secure cloud migration approach for industrial systems and investigates whether it can meet real-time control system requirements without compromising system safety and security. The proposed approach is generic enough to be applied for different industrial sectors with minimal interruption to operations during the cloud migration process. Due to the large number of IIoT devices, manual system monitoring to pin-point issues is a tedious and time-consuming task. This paper also proposes an automated monitoring and management framework for large complex IIoT network that tracks and reports issues using different forms of notifications. Experimental validation on a real microgrid testbed facility concluded that the proposed approach is promising for time-critical industrial systems.

Original language	English
Title of host publication	IEEE 6th World Forum on Internet of Things, New Orleans, United States.
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	6
ISBN (Electronic)	978-1-7281-5503-6
ISBN (Print)	978-1-7281-5504-3
DOIs	https://doi.org/10.1109/WF-IoT48130.2020.9221106
Publication status	Early online date - 13 Oct 2020
Event	IEEE 6th World Forum on Internet of Things - New Orleans, United States Duration: 05 Apr 2020 → 09 Apr 2020 https://wfiot2020.iot.ieee.org/

Conference

Conference	IEEE 6th World Forum on Internet of Things
Abbreviated title	WF-IoT 2020
Country/Territory	United States
City	New Orleans
Period	05/04/2020 → 09/04/2020
Internet address	https://wfiot2020.iot.ieee.org/

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10.1109/WF-IoT48130.2020.9221106Licence: Unspecified

A Secure Cloud Migration, Monitoring and Analytics Framework for Industrial Internet of Things
Copyright 2020 IEEE. This work is made available online in accordance with the publisher’s policies. Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 2.2 MBLicence: Unspecified

Research Institute in Trustworthy Industrial Control Systems (External organisation)
Kieran McLaughlin (Member)
2014 → …
Activity: Membership types › Membership of external research organisation

Cite this

@inproceedings{20d878e22c9842b0bef941da3eb5a070,

title = "A Secure Cloud Migration, Monitoring and Analytics Framework for Industrial Internet of Things",

abstract = "The fourth industrial revolution combines cutting-edge technologies such as Industrial Internet of Things (IIoT) and cloud computing. However, this inevitable revolution faces challenges due to the presence of legacy equipment in industrial systems. Legacy equipment hinders the adoption of emerging cloud technologies due to data privacy, security and interoperability issues. This paper proposes a secure cloud migration approach for industrial systems and investigates whether it can meet real-time control system requirements without compromising system safety and security. The proposed approach is generic enough to be applied for different industrial sectors with minimal interruption to operations during the cloud migration process. Due to the large number of IIoT devices, manual system monitoring to pin-point issues is a tedious and time-consuming task. This paper also proposes an automated monitoring and management framework for large complex IIoT network that tracks and reports issues using different forms of notifications. Experimental validation on a real microgrid testbed facility concluded that the proposed approach is promising for time-critical industrial systems. ",

author = "Rafiullah Khan and Kieran McLaughlin and BooJoong Kang and David Laverty and Sakir Sezer",

year = "2020",

month = oct,

day = "13",

doi = "10.1109/WF-IoT48130.2020.9221106",

language = "English",

isbn = "978-1-7281-5504-3",

booktitle = "IEEE 6th World Forum on Internet of Things, New Orleans, United States.",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "IEEE 6th World Forum on Internet of Things, WF-IoT 2020 ; Conference date: 05-04-2020 Through 09-04-2020",

url = "https://wfiot2020.iot.ieee.org/",

}

Khan, R, McLaughlin, K, Kang, B, Laverty, D & Sezer, S 2020, A Secure Cloud Migration, Monitoring and Analytics Framework for Industrial Internet of Things. in IEEE 6th World Forum on Internet of Things, New Orleans, United States.. Institute of Electrical and Electronics Engineers Inc., IEEE 6th World Forum on Internet of Things, New Orleans, Louisiana, United States, 05/04/2020. https://doi.org/10.1109/WF-IoT48130.2020.9221106

A Secure Cloud Migration, Monitoring and Analytics Framework for Industrial Internet of Things. / Khan, Rafiullah; McLaughlin, Kieran; Kang, BooJoong; Laverty, David ; Sezer, Sakir.

IEEE 6th World Forum on Internet of Things, New Orleans, United States.. Institute of Electrical and Electronics Engineers Inc., 2020.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - A Secure Cloud Migration, Monitoring and Analytics Framework for Industrial Internet of Things

AU - Khan, Rafiullah

AU - McLaughlin, Kieran

AU - Kang, BooJoong

AU - Laverty, David

AU - Sezer, Sakir

PY - 2020/10/13

Y1 - 2020/10/13

N2 - The fourth industrial revolution combines cutting-edge technologies such as Industrial Internet of Things (IIoT) and cloud computing. However, this inevitable revolution faces challenges due to the presence of legacy equipment in industrial systems. Legacy equipment hinders the adoption of emerging cloud technologies due to data privacy, security and interoperability issues. This paper proposes a secure cloud migration approach for industrial systems and investigates whether it can meet real-time control system requirements without compromising system safety and security. The proposed approach is generic enough to be applied for different industrial sectors with minimal interruption to operations during the cloud migration process. Due to the large number of IIoT devices, manual system monitoring to pin-point issues is a tedious and time-consuming task. This paper also proposes an automated monitoring and management framework for large complex IIoT network that tracks and reports issues using different forms of notifications. Experimental validation on a real microgrid testbed facility concluded that the proposed approach is promising for time-critical industrial systems.

AB - The fourth industrial revolution combines cutting-edge technologies such as Industrial Internet of Things (IIoT) and cloud computing. However, this inevitable revolution faces challenges due to the presence of legacy equipment in industrial systems. Legacy equipment hinders the adoption of emerging cloud technologies due to data privacy, security and interoperability issues. This paper proposes a secure cloud migration approach for industrial systems and investigates whether it can meet real-time control system requirements without compromising system safety and security. The proposed approach is generic enough to be applied for different industrial sectors with minimal interruption to operations during the cloud migration process. Due to the large number of IIoT devices, manual system monitoring to pin-point issues is a tedious and time-consuming task. This paper also proposes an automated monitoring and management framework for large complex IIoT network that tracks and reports issues using different forms of notifications. Experimental validation on a real microgrid testbed facility concluded that the proposed approach is promising for time-critical industrial systems.

U2 - 10.1109/WF-IoT48130.2020.9221106

DO - 10.1109/WF-IoT48130.2020.9221106

M3 - Conference contribution

SN - 978-1-7281-5504-3

BT - IEEE 6th World Forum on Internet of Things, New Orleans, United States.

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - IEEE 6th World Forum on Internet of Things

Y2 - 5 April 2020 through 9 April 2020

ER -

A Secure Cloud Migration, Monitoring and Analytics Framework for Industrial Internet of Things

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Research Institute in Trustworthy Industrial Control Systems (External organisation)

Cite this