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

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

Deadline for manuscript submissions: 25 November 2022 | Viewed by 881

Special Issue Editors

Dr. Amir Masoud Rahmani
E-Mail Website
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
E-Mail Website
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
E-Mail Website
Guest Editor
Faculty of Engineering, Canadian university of Dubai, Dubai 04 321 9090, United Arab Emirates
Interests: machine learning; intelligent cybersecurity; AI in healthcare
Dr. Seyedeh Yasaman Hosseini Mirmahaleh
E-Mail Website
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 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 2000 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.


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

Published Papers (1 paper)

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Flexible-Clustering Based on Application Priority to Improve IoMT Efficiency and Dependability
Sustainability 2022, 14(17), 10666; - 26 Aug 2022
Viewed by 340
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 [...] Read more.
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
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