An Approach to Privacy-Preserving Distributed Intelligence for the Internet of Things

Tariq Alsboui; Hussain Al-Aqrabi; Richard Hill; Shamaila Iram

doi:10.5220/0011056400003194

An Approach to Privacy-Preserving Distributed Intelligence for the Internet of Things

Tariq Alsboui, Hussain Al-Aqrabi, Richard Hill, Shamaila Iram

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

2 Citations (Scopus)

Abstract

In the Internet of things (IoT), security and privacy issues are a fundamental challenge determining the successful implementation of many IoT applications. Distributed ledger technology (e.g., Blockchain) offers a great promise to solve these issues. Blockchain-based solutions support security and privacy, yet they involve significant energy due to mining, low throughput, and computational overhead that is not acceptable for IoT resource-constrained devices. In this paper, we propose an energy-efficient Privacy-Preserving Distributed Intelligence approach (PPDI) by adopting the IOTA technology. IOTA is an emerging distributed ledger technology that allows for zero fees transactions for the IoT. The proposed PPDI aims to address the privacy issues in the IoT by using the IOTA Masked Authenticated Messaging (MAM) protocol. MAM ensures privacy by encrypting and granting permission to authorized users to access data. This paper presents a healthcare scenario that demonstrate how IOTA MAM can be used to address the privacy issue in the IoT. The experimental results clearly show that IOTA MAM is a feasible solution that can be used to solve privacy related issues in the IoT domain.

Original language	English
Title of host publication	Proceedings of the 7th International Conference on Internet of Things, Big Data and Security
Subtitle of host publication	IoTBDS 2022
Editors	Denis Bastieri, Gary Wills, Péter Kacsuk, Victor Chang
Publisher	SciTePress
Pages	174-182
Number of pages	9
Volume	1
ISBN (Print)	9789897585647
DOIs	https://doi.org/10.5220/0011056400003194
Publication status	Published - 22 Apr 2022
Event	7th International Conference on Internet of Things, Big Data and Security - Virtual, Portugal Duration: 22 Apr 2022 → 24 Apr 2022 Conference number: 7 https://iotbds.scitevents.org

Publication series

Name	Proceedings of the International Conference on Internet of Things, Big Data and Security
Publisher	Scitepress
ISSN (Print)	2184-4976

Conference

Conference	7th International Conference on Internet of Things, Big Data and Security
Abbreviated title	IoTBDS 2022
Country/Territory	Portugal
Period	22/04/22 → 24/04/22
Internet address	https://iotbds.scitevents.org

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.5220/0011056400003194Licence: CC BY-NC-ND

Cite this

Alsboui, T., Al-Aqrabi, H., Hill, R., & Iram, S. (2022). An Approach to Privacy-Preserving Distributed Intelligence for the Internet of Things. In D. Bastieri, G. Wills, P. Kacsuk, & V. Chang (Eds.), Proceedings of the 7th International Conference on Internet of Things, Big Data and Security: IoTBDS 2022 (Vol. 1, pp. 174-182). (Proceedings of the International Conference on Internet of Things, Big Data and Security). SciTePress. https://doi.org/10.5220/0011056400003194

Alsboui, Tariq ; Al-Aqrabi, Hussain ; Hill, Richard et al. / An Approach to Privacy-Preserving Distributed Intelligence for the Internet of Things. Proceedings of the 7th International Conference on Internet of Things, Big Data and Security: IoTBDS 2022. editor / Denis Bastieri ; Gary Wills ; Péter Kacsuk ; Victor Chang. Vol. 1 SciTePress, 2022. pp. 174-182 (Proceedings of the International Conference on Internet of Things, Big Data and Security).

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title = "An Approach to Privacy-Preserving Distributed Intelligence for the Internet of Things",

abstract = "In the Internet of things (IoT), security and privacy issues are a fundamental challenge determining the successful implementation of many IoT applications. Distributed ledger technology (e.g., Blockchain) offers a great promise to solve these issues. Blockchain-based solutions support security and privacy, yet they involve significant energy due to mining, low throughput, and computational overhead that is not acceptable for IoT resource-constrained devices. In this paper, we propose an energy-efficient Privacy-Preserving Distributed Intelligence approach (PPDI) by adopting the IOTA technology. IOTA is an emerging distributed ledger technology that allows for zero fees transactions for the IoT. The proposed PPDI aims to address the privacy issues in the IoT by using the IOTA Masked Authenticated Messaging (MAM) protocol. MAM ensures privacy by encrypting and granting permission to authorized users to access data. This paper presents a healthcare scenario that demonstrate how IOTA MAM can be used to address the privacy issue in the IoT. The experimental results clearly show that IOTA MAM is a feasible solution that can be used to solve privacy related issues in the IoT domain.",

keywords = "Internet of Things (IoT), IOTA Tangle, IOTA, Distributed Ledger Technology (DLT), Security and privacy, Masked Authenticated Messaging (MAM), Privacy",

author = "Tariq Alsboui and Hussain Al-Aqrabi and Richard Hill and Shamaila Iram",

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Alsboui, T, Al-Aqrabi, H, Hill, R & Iram, S 2022, An Approach to Privacy-Preserving Distributed Intelligence for the Internet of Things. in D Bastieri, G Wills, P Kacsuk & V Chang (eds), Proceedings of the 7th International Conference on Internet of Things, Big Data and Security: IoTBDS 2022. vol. 1, Proceedings of the International Conference on Internet of Things, Big Data and Security, SciTePress, pp. 174-182, 7th International Conference on Internet of Things, Big Data and Security, Portugal, 22/04/22. https://doi.org/10.5220/0011056400003194

An Approach to Privacy-Preserving Distributed Intelligence for the Internet of Things. / Alsboui, Tariq; Al-Aqrabi, Hussain; Hill, Richard et al.

Proceedings of the 7th International Conference on Internet of Things, Big Data and Security: IoTBDS 2022. ed. / Denis Bastieri; Gary Wills; Péter Kacsuk; Victor Chang. Vol. 1 SciTePress, 2022. p. 174-182 (Proceedings of the International Conference on Internet of Things, Big Data and Security).

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

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AB - In the Internet of things (IoT), security and privacy issues are a fundamental challenge determining the successful implementation of many IoT applications. Distributed ledger technology (e.g., Blockchain) offers a great promise to solve these issues. Blockchain-based solutions support security and privacy, yet they involve significant energy due to mining, low throughput, and computational overhead that is not acceptable for IoT resource-constrained devices. In this paper, we propose an energy-efficient Privacy-Preserving Distributed Intelligence approach (PPDI) by adopting the IOTA technology. IOTA is an emerging distributed ledger technology that allows for zero fees transactions for the IoT. The proposed PPDI aims to address the privacy issues in the IoT by using the IOTA Masked Authenticated Messaging (MAM) protocol. MAM ensures privacy by encrypting and granting permission to authorized users to access data. This paper presents a healthcare scenario that demonstrate how IOTA MAM can be used to address the privacy issue in the IoT. The experimental results clearly show that IOTA MAM is a feasible solution that can be used to solve privacy related issues in the IoT domain.

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Alsboui T, Al-Aqrabi H, Hill R , Iram S. An Approach to Privacy-Preserving Distributed Intelligence for the Internet of Things. In Bastieri D, Wills G, Kacsuk P, Chang V, editors, Proceedings of the 7th International Conference on Internet of Things, Big Data and Security: IoTBDS 2022. Vol. 1. SciTePress. 2022. p. 174-182. (Proceedings of the International Conference on Internet of Things, Big Data and Security). doi: 10.5220/0011056400003194

An Approach to Privacy-Preserving Distributed Intelligence for the Internet of Things

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