Insights into Internet of Medical Things (IoMT): Data fusion, security issues and potential solutions

被引:74
作者
Ahmed, Shams Forruque [1 ]
Bin Alam, Md. Sakib [2 ]
Afrin, Shaila [1 ]
Rafa, Sabiha Jannat [1 ]
Rafa, Nazifa [3 ]
Gandomi, Amir H. [4 ,5 ]
机构
[1] Asian Univ Women, Sci & Math Program, Chittagong 4000, Bangladesh
[2] Asian Inst Technol, Data Sci & Artificial Intelligence, Chang Wat Pathum Thani 12120, Thailand
[3] Univ Cambridge, Dept Geog, Downing Pl, Cambridge CB2 3EN, England
[4] Univ Technol Sydney, Fac Engn & Informat Technol, Sydney, NSW 2007, Australia
[5] Obuda Univ, Univ Res & Innovat Ctr EKIK, H-1034 Budapest, Hungary
关键词
IoMT; Internet of medical things; Data fusion; Smart healthcare; IoT; Internet of Things; Blockchain; USER AUTHENTICATION SCHEME; WIRELESS COMMUNICATION; PRIVACY ISSUES; CHALLENGES; DEVICES; IOT; LIGHTWEIGHT; NETWORKS; SENSORS; ATTACKS;
D O I
10.1016/j.inffus.2023.102060
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The Internet of Medical Things (IoMT) has created a wide range of opportunities for knowledge exchange in numerous industries. The opportunities include patient empowerment, healthcare collaboration, medical education and training, remote monitoring and telemedicine, customized treatment plans, data sharing for innovation, continuous medical learning, supply chain management, public health initiatives, wearable health devices, and quality improvement initiatives. However, the adoption of IoMT faces numerous challenges regarding interoperability, data privacy, security, regulatory, and infrastructure costs. This paper aims to address the implications of data fusion in IoMT, as well as the associated security challenges and their potential solutions, which are lacking in the literature. Data collected from IoMT devices has a direct impact on the accuracy of predictions because of its quality, quantity, and relevance. With an accuracy of 99.53 % to 99.99 %, the Epilepsy seizure detector-based Naive Bayes (ESDNB) algorithm is found to be the most effective for detecting epileptic seizures in IoMT networks. However, the way data are stored must also undergo a major revolution, and all phases-collection, protection, and storage-need to be improved. The standardization of architecture and security measures may improve the detection of security threats and compromises. Methods to detect malware in cross platforms is also an avenue for future research that can effectively tackle the heterogeneity of the IoMT systems. Cryptography and blockchain technology have shown to be promising ways to increase the security of an IoMT-based system. The findings of this review will assist a wide variety of stakeholders in the healthcare ecosystem.
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页数:20
相关论文
共 149 条
[91]   Lightweight authentication protocol for e-health clouds in IoT-based applications through 5G technology [J].
Minahil ;
Ayub, Muhammad Faizan ;
Mahmood, Khalid ;
Kumari, Saru ;
Sangaiah, Arun Kumar .
DIGITAL COMMUNICATIONS AND NETWORKS, 2021, 7 (02) :235-244
[92]   Securing IoTs in distributed blockchain: Analysis, requirements and open issues [J].
Moin, Sana ;
Karim, Ahmad ;
Safdar, Zanab ;
Safdar, Kalsoom ;
Ahmed, Ejaz ;
Imran, Muhammad .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2019, 100 :325-343
[93]  
Mubashar A., 2021, Storage and Proximity Management for Centralized Personal Health Records Using an IPFS-Based Optimization Algorithm, V31, DOI [10.1142/S0218126622500104, DOI 10.1142/S0218126622500104]
[94]   A comprehensive survey on multimodal medical signals fusion for smart healthcare systems [J].
Muhammad, Ghulam ;
Alshehri, Fatima ;
Karray, Fakhri ;
El Saddik, Abdulmotaleb ;
Alsulaiman, Mansour ;
Falk, Tiago H. .
INFORMATION FUSION, 2021, 76 :355-375
[95]   Smart Vest for Respiratory Rate Monitoring of COPD Patients Based on Non-Contact Capacitive Sensing [J].
Naranjo-Hernandez, David ;
Talaminos-Barroso, Alejandro ;
Reina-Tosina, Javier ;
Roa, Laura M. ;
Barbarov-Rostan, Gerardo ;
Cejudo-Ramos, Pilar ;
Marquez-Martin, Eduardo ;
Ortega-Ruiz, Francisco .
SENSORS, 2018, 18 (07)
[96]   Securing Fog Computing for Internet of Things Applications: Challenges and Solutions [J].
Ni, Jianbing ;
Zhang, Kuan ;
Lin, Xiaodong ;
Shen, Xuemin .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2018, 20 (01) :601-628
[97]   Blockchain-Empowered Secure and Privacy-Preserving Health Data Sharing in Edge-Based IoMT [J].
Nie, Xueli ;
Zhang, Aiqing ;
Chen, Jindou ;
Qu, Youyang ;
Yu, Shui .
SECURITY AND COMMUNICATION NETWORKS, 2022, 2022
[98]   Cyberentity Security in the Internet of Things [J].
Ning, Huansheng ;
Liu, Hong ;
Yang, Laurence T. .
COMPUTER, 2013, 46 (04) :46-53
[99]   An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0 [J].
Pace, Pasquale ;
Aloi, Gianluca ;
Gravina, Raffaele ;
Caliciuri, Giuseppe ;
Fortino, Giancarlo ;
Liotta, Antonio .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2019, 15 (01) :481-489
[100]   Enhanced Deep Learning Assisted Convolutional Neural Network for Heart Disease Prediction on the Internet of Medical Things Platform [J].
Pan, Yuanyuan ;
Fu, Minghuan ;
Cheng, Biao ;
Tao, Xuefei ;
Guo, Jing .
IEEE ACCESS, 2020, 8 :189503-189512