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用于智能建筑中长期护理服务的安全机器人物联网(IoRT)。

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

作者信息

Chang Shih-Hao, Hsia Chih-Hsien, Hong Wei-Zhi

机构信息

Department of Computer Science and Information Engineering, National Taipei University of Technology, Taipei, Taiwan.

Department of Computer Science and Information Engineering, National Ilan University, Yilan, Taiwan.

出版信息

J Supercomput. 2023;79(5):5276-5290. doi: 10.1007/s11227-022-04845-1. Epub 2022 Oct 13.

DOI:10.1007/s11227-022-04845-1
PMID:36258682
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9559120/
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.

摘要

长期护理是指因身体或精神状况而患有慢性疾病或残疾的老年人所获得的任何医疗和非医疗支持。由于长期护理保险费用不菲,因此可以使用低成本设备和传感器来创建医疗辅助系统,以降低人力维护成本。医疗信息保护下的安全和隐私要求是医疗物联网(IoMT)数据传输的关键问题。在本文中,我们为长期护理系统设计了一个医疗物联网安全机器人。这个医疗物联网安全机器人的目标是提供居民私人信息的安全传输。它由三层组成,即收集层、加密层和传输层。医疗物联网安全机器人的功能是首先从患者或老年人那里收集数据,然后提供高效的数据加密,并提供安全的数据传输机制,将有价值的数据发送到云端。这个医疗物联网安全机器人还具有服务器认证机制以及支持物联网和医疗物联网设备的检查功能。我们的评估结果表明,即使我们使用像树莓派这样的低功耗设备,AES算法在9毫秒内也能实现100 - 100KB字节的加密和解密,这比需要大约104毫秒的ECC算法要好得多。此外,我们发现AES解密100字节数据仅需0.00015秒,这比需要0.09秒的ECC算法快得多。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/17328fd370c0/11227_2022_4845_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/566a828f42ac/11227_2022_4845_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/b96d38625f43/11227_2022_4845_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/12bf18d90eef/11227_2022_4845_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/b6f640bce42f/11227_2022_4845_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/63c4378a1593/11227_2022_4845_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/2a4438fe4f50/11227_2022_4845_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/9c5dea021178/11227_2022_4845_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/1cccf0a48126/11227_2022_4845_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/17328fd370c0/11227_2022_4845_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/566a828f42ac/11227_2022_4845_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/b96d38625f43/11227_2022_4845_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/12bf18d90eef/11227_2022_4845_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/b6f640bce42f/11227_2022_4845_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/63c4378a1593/11227_2022_4845_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/2a4438fe4f50/11227_2022_4845_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/9c5dea021178/11227_2022_4845_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/1cccf0a48126/11227_2022_4845_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce1d/9559120/17328fd370c0/11227_2022_4845_Fig9_HTML.jpg

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