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A secured internet of robotic things (IoRT) for long-term care services in a smart building.

Authors :
Chang SH
Hsia CH
Hong WZ
Source :
The Journal of supercomputing [J Supercomput] 2023; Vol. 79 (5), pp. 5276-5290. Date of Electronic Publication: 2022 Oct 13.
Publication Year :
2023

Abstract

Long-term care refers to any support, both medical and non-medical, provided to the elderly with a chronic illness or disability due to physical or mental conditions. Since the cost of long-term care insurance is not inexpensive, low-cost devices and sensors can be used to create medical assistance systems to reduce human maintenance costs. The requirement of security and privacy under healthcare information protection is a critical issue for internet of medical things (IoMT) data transmission. In this paper, we designed an IoMT security robot for a long-term care system. The goal of this IoMT security robot is to provide secure transmission of the residents' private information. It is composed of three layers, namely, collection, encryption, and transmission. The function of the IoMT security robot is to first collect data from the patient or the elderly, then provide efficient data encryption, and deliver secured data transmission mechanisms to send the valuable data to the cloud. This IoMT security robot also has a server authentication mechanism, and a support IoT and IoMT devices inspection function. Our evaluation results showed that even when we utilized a low power consumption device like Raspberry Pi, AES algorithm achieved an encrypt and decrypt of 100-100 K bytes under 9 ms, which is a lot better than ECC, which takes about 104 ms. Further, we found that the AES only takes 0.00015 s to decrypt 100 Bytes data, which is way faster than the ECC algorithm, which takes 0.09 s.<br />Competing Interests: Conflict of interestThe authors declare no conflict of interest.<br /> (© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, corrected publication 2022Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Details

Language :
English
ISSN :
0920-8542
Volume :
79
Issue :
5
Database :
MEDLINE
Journal :
The Journal of supercomputing
Publication Type :
Academic Journal
Accession number :
36258682
Full Text :
https://doi.org/10.1007/s11227-022-04845-1