AI-enabled Secure Microservices in Edge Computing: Opportunities and Challenges

Al-Doghman, F; Moustafa, N; Khalil, I; Tari, Z; Zomaya, A

AI-enabled Secure Microservices in Edge Computing: Opportunities and Challenges

Al-Doghman, F

Moustafa, N Khalil, I Tari, Z Zomaya, A

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Publisher:: Institute of Electrical and Electronics Engineers (IEEE)
Publication Type:: Journal Article
Citation:: IEEE Transactions on Services Computing, 2022, PP, (99), pp. 1-1
Issue Date:: 2022-01-01

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Field	Value	Language
dc.contributor.author	Al-Doghman, F https://orcid.org/0000-0002-1020-8097
dc.contributor.author	Moustafa, N
dc.contributor.author	Khalil, I
dc.contributor.author	Tari, Z
dc.contributor.author	Zomaya, A
dc.date.accessioned	2023-03-20T00:45:33Z
dc.date.available	2023-03-20T00:45:33Z
dc.date.issued	2022-01-01
dc.identifier.citation	IEEE Transactions on Services Computing, 2022, PP, (99), pp. 1-1
dc.identifier.issn	2372-0204
dc.identifier.issn	1939-1374
dc.identifier.uri	http://hdl.handle.net/10453/167672
dc.description.abstract	The paradigm of edge computing has formed an innovative scope within the domain of IoT through expanding the services of the cloud to the network edge to design distributed architectures and securely enhance decision-making applications. Due to the heterogeneous of edge Computing, edge applications are required to be developed as a set of lightweight and interdependent modules. As this concept aligns with the objectives of microservice architecture, effective implementation of microservices-based edge applications within IoT networks has the prospective of fully leveraging edge nodes capabilities. Deploying microservices at IoT edge faces plenty of challenges associated with security and privacy. Advances in AI, and the easy access to resources with powerful computing providing opportunities for deriving precise models and developing different intelligent applications at the edge of network. In this study, an extensive survey is presented for securing edge computing-based AI Microservices to elucidate the challenges of IoT management and enable secure decision-making systems at the edge. We present recent research studies on edge AI and microservices orchestration and highlight key requirements as well as challenges of securing Microservices at IoT edge. We also propose a Microservices-based edge framework that provides secure edge AI algorithms as Microservices utilizing the containerization technology.
dc.language	en
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartof	IEEE Transactions on Services Computing
dc.relation.isbasedon	10.1109/TSC.2022.3155447
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0803 Computer Software, 0805 Distributed Computing, 0806 Information Systems
dc.title	AI-enabled Secure Microservices in Edge Computing: Opportunities and Challenges
dc.type	Journal Article
utslib.citation.volume	PP
utslib.for	0803 Computer Software
utslib.for	0805 Distributed Computing
utslib.for	0806 Information Systems
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2023-03-20T00:45:32Z
pubs.issue	99
pubs.publication-status	Published
pubs.volume	PP
utslib.citation.issue	99

Abstract:

The paradigm of edge computing has formed an innovative scope within the domain of IoT through expanding the services of the cloud to the network edge to design distributed architectures and securely enhance decision-making applications. Due to the heterogeneous of edge Computing, edge applications are required to be developed as a set of lightweight and interdependent modules. As this concept aligns with the objectives of microservice architecture, effective implementation of microservices-based edge applications within IoT networks has the prospective of fully leveraging edge nodes capabilities. Deploying microservices at IoT edge faces plenty of challenges associated with security and privacy. Advances in AI, and the easy access to resources with powerful computing providing opportunities for deriving precise models and developing different intelligent applications at the edge of network. In this study, an extensive survey is presented for securing edge computing-based AI Microservices to elucidate the challenges of IoT management and enable secure decision-making systems at the edge. We present recent research studies on edge AI and microservices orchestration and highlight key requirements as well as challenges of securing Microservices at IoT edge. We also propose a Microservices-based edge framework that provides secure edge AI algorithms as Microservices utilizing the containerization technology.

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http://hdl.handle.net/10453/167672