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  5. ESSMAR: Edge Supportive Secure Mobile Augmented Reality Architecture for Healthcare
 
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ESSMAR: Edge Supportive Secure Mobile Augmented Reality Architecture for Healthcare

Author(s)
Braeken, An  
Porambage, Pawani  
Puvaneswaran, Amirthan  
Liyanage, Madhusanka  
Uri
http://hdl.handle.net/10197/12098
Date Issued
2020-11-26
Date Available
2021-04-15T15:40:44Z
Abstract
The recent advances in mobile devices and wireless communication sector transformed Mobile Augmented Reality (MAR) from science fiction to reality. Among the other MAR use cases, the incorporation of this MAR technology in the healthcare sector can elevate the quality of diagnosis and treatment for the patients. However, due to the highly sensitive nature of the data available in this process, it is also highly vulnerable to all types of security threats. In this paper, an edge-based secure architecture is presented for a MAR healthcare application. Based on the ESSMAR architecture, a secure key management scheme is proposed for both the registration and authentication phases. Then the security of the proposed scheme is validated using formal and informal verification methods.
Sponsorship
Enterprise Ireland
European Commission
Irish Research Council
Science Foundation Ireland
University College Dublin
Other Sponsorship
Business Finland
Type of Material
Conference Publication
Publisher
IEEE
Copyright (Published Version)
2020 IEEE
Subjects

Wireless communicatio...

Cloud computing

Authentication

Computer architecture...

Medical services

Security

Augmented reality

DOI
10.1109/cloudtech49835.2020.9365909
Web versions
http://macc.ma/cloudtech20/
Language
English
Status of Item
Peer reviewed
Journal
Essaaidi, M., Zbakh, M. and Ouacha, A. (eds.) Proceedings of 2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech’20)
Conference Details
The 5th International Conference on Cloud Computing and Artificial Intelligence (CloudTech 2020), Marrakesh, Morocco (held online due to Coronavirus outbreak), 24-26 November 2020
ISBN
978-1-7281-6175-4
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
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Name

Latincom_2019_MAR_Security.pdf

Size

1 MB

Format

Adobe PDF

Checksum (MD5)

2cffa9412af91f9947485108c8efb630

Owning collection
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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