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Sustainability/Privacy-Preserving of IoT-Based Application in Smart Healthcare

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Health, Well-Being and Sustainability".

Deadline for manuscript submissions: closed (25 November 2022) | Viewed by 21534

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Special Issue Editors

Dr. Amir Masoud Rahmani

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Guest Editor

Future Technology Research Center, National Yunlin University of Science and Technology, Douliou 64002, Taiwan
Interests: distributed systems; Internet of Things and evolutionary computing
Special Issues, Collections and Topics in MDPI journals

Dr. Stavros Shiaeles

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Guest Editor

Cyber Security Research Group, School of Computing University of Portsmouth, Portsmouth PO1 2UP, UK
Interests: AI cybersecurity; intrusion detection and response; botnets; malware analysis; forensics
Special Issues, Collections and Topics in MDPI journals

Dr. Firuz Kamalov

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Guest Editor

Faculty of Engineering, Canadian University Dubai, Dubai, United Arab Emirates
Interests: operator algebras; machine learning
Special Issues, Collections and Topics in MDPI journals

Dr. Seyedeh Yasaman Hosseini Mirmahaleh

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Guest Editor

Department of Electrical Engineering, Science and Technology, Lille University, 59000 Lille, France
Interests: computer architecture; Network on Chip; Multi and Many-core processors; deep learning accelerator

Special Issue Information

Dear Colleagues,

Subject and Scope:

Internet of Things (IoT) systems are gaining much attention in various fields, such as smart healthcare, etc. In the ecology of these systems, any gadgets or devices that connect to a service provider's network are considered part of the IoT network. Through leveraging IoT, the environment can be monitored by processing shared sensed data of IoT devices. The sensed data can be exchanged among connected objects, or "Things", and remote locations for storage and processing, which permits the collection of a large amount of data about patients, conditions, and other things in smart healthcare. In smart healthcare, the whole system is known as IoMT (Internet of Medical Things). The IoT-based systems in smart healthcare solutions are designed to resolve medical treatment problems, allowing people to access them anywhere and at any time. However, IoMT solutions, a type of big data generator, have several challenges, such as lack of effective solutions for security, privacy-preservation, inaccurate device updates, user unawareness, and active device tracking capabilities, which require management and access control. The lack of efficient security and privacy approaches leads IoMT systems to have illegal access and be misused by unwanted parties. In brief, having access to many medical data could be a lucrative resource for hackers.

Given that IoMT is a key part of the present and the future of smart healthcare, security and privacy play a vital role in its success. Through observation, we have found that several solutions have been introduced to overcome these difficulties in recent years; however, they are not enough. In this Special Issue, we aim to address the security and privacy challenges emerging from deploying IoMT in smart healthcare, emphasizing IoMT frameworks, networking, infrastructures, and protocols. In addition, the Special Issue provides an up-to-date statement of the current research progress in IoMT security, privacy challenges, and approaches for protecting medical data and the sustainability of IoT-based healthcare.

The mentioned challenges and problems of deploying IoMT-based applications had created an opportunity for the researchers to attend to the various authentication protocols and define a novel approach to satisfy security and protect the patients' private records. Additionally, deep learning accelerator-based systems supported the challenges of processing data in the physical layer of the Internet of Medical Things, including bandwidth and memory requirements, communication delay, and energy efficiency. The various reliable, available, and trust models covered the relationship between the patients, doctors, and other healthcare service providers to provide a secure platform for their communications. The studies almost focused on timely detecting the active and passive attacks by the intruders, in which the failed nodes can lead to problems with reporting incorrect data and information. By providing the hardware-based approaches to detect or predict defective nodes of the Internet of Medical Things, a case study can prevent from distributing malicious data between the application's components. The researchers can define the priority to propose an idea for improving IoMT performance and cost based on the application and the requesters’ situation, which consist of providing secure or trusted healthcare services or timely service with minimal possible security. By deploying the studies in the field of the human’s brain neuron structure and their patterns to tackle some specific diseases, their structure and communication between them (such as distributing cholesterol and falling or rising the number of amyloids plucks) can help to predict the failure area of a set of IoMT-application's nodes. The main standpoints besides the mentioned challenges of IoMT and healthcare systems include:

Considering defective components and hardware redundancy for providing a reliable platform;
Analyzing and defining priority concepts to decision-making and providing a healthcare service based on IoMT-application and the requesters’ situation;
Investigating the role of human brain neuron structure and their pattern to communication between them on improving the efficiency of IoT.

Submission Guideline:

Original articles that have not been published elsewhere are sought for this Special Issue. The "Submit Online" button on the journal's submission page allows authors to follow the journal's formatting and submission instructions. The authors should mention that their article is for this special issue in the cover letter.

Topics of Interest:

The following topics are interesting, but not limited to:

Innovative techniques for addressing Sustainability/privacy in IoMT;
Prevention systems and cyber-attacks detection for IoMT;
Trust-based solutions for the IoMT;
Biometric modalities involved in IoMT;
Sustainable and Reliability approaches in IoMT;
Machine Learning and Deep Learning for improving IoMT Sustainability/Privacy;
Social considerations, ethics, legal, and in IoMT Sustainability/Privacy.

We look forward to receiving your contributions.

Dr. Amir Masoud Rahmani
Dr. Stavros Shiaeles
Dr. Firuz Kamalov
Dr. Seyedeh Yasaman Hosseini Mirmahaleh
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Internet of Medical Things (IoMT)
reliability
trust
security
deep learning
Neuronal Network (NN)

Published Papers (7 papers)

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Research

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17 pages, 2073 KiB

Open AccessArticle

An Intelligent Health Care System in Fog Platform with Optimized Performance

by Subhranshu Sekhar Tripathy, Mamata Rath, Niva Tripathy, Diptendu Sinha Roy, John Sharmila Anand Francis and Sujit Bebortta

Sustainability 2023, 15(3), 1862; https://doi.org/10.3390/su15031862 - 18 Jan 2023

Cited by 7 | Viewed by 1872

Abstract

Cloud computing delivers services through the Internet and enables the deployment of a diversity of apps to provide services to many businesses. At present, the low scalability of these cloud frameworks is their primary obstacle. As a result, they are unable to satisfy the demands of centralized computer systems, which are based on the Internet of Things (IoT). Applications such as disease surveillance and tracking and monitoring systems, which are highly latency sensitive, demand the computation of the Big Data communicated to centralized databases and from databases to cloud data centers, resulting in system performance loss. Recent concepts, such as fog and edge computing, offer novel approaches to data processing by relocating the processing power and other resources closer to the end user, thereby reducing latency and maximizing energy efficiency. Existing fog models, on the other hand, have a number of limitations and tend to prioritize either the precision of their findings or a faster response time, but not both. For the purpose of applying a healthcare solution in the real world, we developed and implemented a one-of-a-kind architecture that integrates quartet deep learning with edge computing devices. The paradigm that has been developed delivers health management as a fog service through the Internet of Things (IoT) devices and efficiently organizes the data from patients based on the requirements of the user. FogBus, a fog-enabled cloud framework, is used to measure the effectiveness of the proposed structure in regards to resource usage, network throughput, congestion, precision, and runtime. To maximize the QoS or forecast the accuracy in different fog computing settings and for different user requirements, the suggested technique can be set up to run in a number of different modes. Full article

(This article belongs to the Special Issue Sustainability/Privacy-Preserving of IoT-Based Application in Smart Healthcare)

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18 pages, 702 KiB

Open AccessArticle

A Particle Swarm Optimization and Deep Learning Approach for Intrusion Detection System in Internet of Medical Things

by Rajasekhar Chaganti, Azrour Mourade, Vinayakumar Ravi, Naga Vemprala, Amit Dua and Bharat Bhushan

Sustainability 2022, 14(19), 12828; https://doi.org/10.3390/su141912828 - 08 Oct 2022

Cited by 30 | Viewed by 3021

Abstract

Integrating the internet of things (IoT) in medical applications has significantly improved healthcare operations and patient treatment activities. Real-time patient monitoring and remote diagnostics allow the physician to serve more patients and save human lives using internet of medical things (IoMT) technology. However, IoMT devices are prone to cyber attacks, and security and privacy have been a concern. The IoMT devices operate on low computing and low memory, and implementing security technology on IoMT devices is not feasible. In this article, we propose particle swarm optimization deep neural network (PSO-DNN) for implementing an effective and accurate intrusion detection system in IoMT. Our approach outperforms the state of the art with an accuracy of 96% to detect network intrusions using the combined network traffic and patient’s sensing dataset. We also present an extensive analysis of using various Machine Learning(ML) and Deep Learning (DL) techniques for network intrusion detection in IoMT and confirm that DL models perform slightly better than ML models. Full article

(This article belongs to the Special Issue Sustainability/Privacy-Preserving of IoT-Based Application in Smart Healthcare)

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31 pages, 6721 KiB

Open AccessArticle

Flexible-Clustering Based on Application Priority to Improve IoMT Efficiency and Dependability

by Amir Masoud Rahmani and Seyedeh Yasaman Hosseini Mirmahaleh

Sustainability 2022, 14(17), 10666; https://doi.org/10.3390/su141710666 - 26 Aug 2022

Cited by 3 | Viewed by 1234

Abstract

The Internet of Medical Things (IoMT) has overcome the privacy challenges of E-healthcare-based Internet of Things (IoT) systems to protect the joined people’s private records to IoMT infrastructures and support their information security in different layers. By deploying various medical applications, security and privacy are challenging for the IoMT via rising communications between its layers and nodes. Some case studies aimed to solve the issues and provided various methods and protocols to identify the malicious data and information, which had almost overlooked application and service priority to targeting the research and satisfying security. We addressed the dependability and privacy problems of IoMT-based applications by presenting an intelligent algorithm for node mapping and flexible clustering (NFC) via defining a graph and employing a neural network (NN). This work proposes a flexible clustering method to categorize the healthcare service providers for timely detecting faults and identifying the proper servers to join the cluster by considering service and application priority. We improve the application dependability and privacy by about 77.3–83.2% via pruning the defective nodes and employing the neighbor components to support faulty devices’ role. By removing the failed or faulty nodes, the study reduces communication delay and energy consumption, approximately 19.3–21.7% and 10.3–11.8%, respectively. Full article

(This article belongs to the Special Issue Sustainability/Privacy-Preserving of IoT-Based Application in Smart Healthcare)

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25 pages, 1607 KiB

Open AccessReview

Towards a Secure and Sustainable Internet of Medical Things (IoMT): Requirements, Design Challenges, Security Techniques, and Future Trends

by Bharat Bhushan, Avinash Kumar, Ambuj Kumar Agarwal, Amit Kumar, Pronaya Bhattacharya and Arun Kumar

Sustainability 2023, 15(7), 6177; https://doi.org/10.3390/su15076177 - 03 Apr 2023

Cited by 18 | Viewed by 4170

Abstract

Recent advances in machine-to-machine (M2M) communications, mini-hardware manufacturing, and micro computing have led to the development of the Internet of Things (IoT). The IoT is integrated with medical devices in order to enable better treatment, cost-effective medical solutions, improved patient monitoring, and enhanced personalized healthcare. This has led to the development of more complex and heterogeneous Internet of Medical Things (IoMT) systems that have their own operating systems and protocols. Even though such pervasive and low-cost sensing devices can bring about enormous changes in the healthcare sector, these are prone to numerous security and privacy issues. Security is thus a major challenge in these critical systems, one that inhibits their widespread adoption. However, significant inroads have been made by the on-going research, which powers the IoMT applications by incorporating prevalent security measures. In this regard, this paper highlights the significance of implementing key security measures, and essential aspects of the IoMT that make it useful for interconnecting various internal and external working domains of healthcare. This paper presents state-of-the-art techniques for securing IoMT systems, in terms of data transmission, collection, and storage. Furthermore, the paper also explores various security requirements, inherent design challenges, and various security techniques that could make the IoMT more secure and sustainable. Finally, the paper gives a panoramic view of the current status of research in the field and outlines some future research directions in this area. Full article

(This article belongs to the Special Issue Sustainability/Privacy-Preserving of IoT-Based Application in Smart Healthcare)

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22 pages, 1967 KiB

Open AccessReview

Internet of Medical Things Privacy and Security: Challenges, Solutions, and Future Trends from a New Perspective

by Firuz Kamalov, Behrouz Pourghebleh, Mehdi Gheisari, Yang Liu and Sherif Moussa

Sustainability 2023, 15(4), 3317; https://doi.org/10.3390/su15043317 - 10 Feb 2023

Cited by 50 | Viewed by 4169

Abstract

The Internet of Medical Things (IoMT), an application of the Internet of Things (IoT) in the medical domain, allows data to be transmitted across communication networks. In particular, IoMT can help improve the quality of life of citizens and older people by monitoring and managing the body’s vital signs, including blood pressure, temperature, heart rate, and others. Since IoMT has become the main platform for information exchange and making high-level decisions, it is necessary to guarantee its reliability and security. The growth of IoMT in recent decades has attracted the interest of many experts. This study provides an in-depth analysis of IoT and IoMT by focusing on security concerns from different points of view, making this comprehensive survey unique compared to other existing studies. A total of 187 articles from 2010 to 2022 are collected and categorized according to the type of applications, year of publications, variety of applications, and other novel perspectives. We compare the current studies based on the above criteria and provide a comprehensive analysis to pave the way for researchers working in this area. In addition, we highlight the trends and future work. We have found that blockchain, as a key technology, has solved many problems of security, authentication, and maintenance of IoT systems due to the decentralized nature of the blockchain. In the current study, this technology is examined from the application fields’ points of view, especially in the health sector, due to its additional importance compared to other fields. Full article

(This article belongs to the Special Issue Sustainability/Privacy-Preserving of IoT-Based Application in Smart Healthcare)

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17 pages, 1844 KiB

Open AccessReview

Blockchain-Based Solutions Supporting Reliable Healthcare for Fog Computing and Internet of Medical Things (IoMT) Integration

by Shadab Alam, Mohammed Shuaib, Sadaf Ahmad, Dushantha Nalin K. Jayakody, Ammar Muthanna, Salil Bharany and Ibrahim A. Elgendy

Sustainability 2022, 14(22), 15312; https://doi.org/10.3390/su142215312 - 18 Nov 2022

Cited by 26 | Viewed by 2983

Abstract

The Internet of Things (IoT) has radically transformed how patient information and healthcare monitoring are monitored and recorded and has revolutionized the area by ensuring regular 24 × 7 tracking without costly and restricted human resources and with a low mistake probability. The Internet of Medical Things (IoMT) is a subsection of the Internet of things (IoT) that uses medical equipment as things or nodes to enable cost-effective and efficient patient monitoring and recording. The IoMT can cope with a wide range of problems, including observing patients in hospitals, monitoring patients in their homes, and assisting consulting physicians and nurses in monitoring health conditions at regular intervals and issuing warning signals if emergency care is necessary. EEG signals, electrocardiograms (ECGs), blood sugar levels, blood pressure levels, and other conditions can be examined. In crucial situations, quick and real-time analysis is essential, and failure to provide careful attention can be fatal. A cloud-based IoT platform cannot handle these latency-sensitive conditions. Fog computing (FC) is a novel paradigm for assigning, processing, and storing resources to IoT devices with limited resources. Where substantial processing power or storage is required, all nodes in a fog computing scheme can delegate their jobs to local fog nodes rather than forwarding them to the cloud module at a greater distance. Identifying potential security risks and putting in place adequate security measures are critical. This work aims to examine a blockchain (BC) as a potential tool for mitigating the impact of these difficulties in conjunction with fog computing. This research shows that blockchain can overcome fog computing’s privacy and security concerns. It also discusses blockchain’s issues and limitations from the perspective of fog computing (FC) and the IoMT. Full article

(This article belongs to the Special Issue Sustainability/Privacy-Preserving of IoT-Based Application in Smart Healthcare)

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Other

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29 pages, 2057 KiB

Open AccessSystematic Review

Internet of Medical Things in the COVID-19 Era: A Systematic Literature Review

by Atefeh Hemmati and Amir Masoud Rahmani

Sustainability 2022, 14(19), 12637; https://doi.org/10.3390/su141912637 - 04 Oct 2022

Cited by 4 | Viewed by 2592

Abstract

In recent years, the medical industry has rapidly modernized, incorporating technology to aid in accelerating and simplifying procedures for better accuracy. This technology is becoming more interconnected to create a larger network known as the Internet of Medical Things (IoMT) that can combat the pandemic’s spread. In other words, IoMT emphasizes health applications while maintaining the core concept of the Internet of Things (IoT). The further spread of Coronavirus Disease-2019 (COVID-19) can be halted by employing it. Consequently, this paper uses the Systematic Literature Review (SLR) methodology to evaluate recently published articles in the IoMT domain during the COVID-19 era. Between 2019 and 2022, we analyzed 41 studies. An analysis of the evaluation criteria reveals that the delay factor comprises 38% of the evaluation criteria, the highest percentage because a low-delay IoMT device has a quick response time between the time a request is made and the time a response is received. Moreover, the performance factor accounts for 22%, the accuracy factor accounts for 28%, the security factor for 6%, and the cost factor for 6%. Finally, we concentrate on open issues and future research challenges in IoMT during the COVID-19 era. Full article

(This article belongs to the Special Issue Sustainability/Privacy-Preserving of IoT-Based Application in Smart Healthcare)

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