Security Issues for IoT Healthcare Applications: Recent Trends and Practices

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 8558

Special Issue Editors


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Guest Editor
Department of Computer Science, Kristianstad University, SE-29188 Kristianstad, Sweden
Interests: AI; smart and wearable healthcare; IoT; 5G-IoT devices authentication; edge computing and big data analytics
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Guest Editor

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Guest Editor
1. College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, China
2. Computer Technology and Engineering, Benazir Bhutto Shaheed University Lyari, Karachi 75660, Pakistan
Interests: blockchain; IoMT; healthcare; security; AI; ML; body area network

Special Issue Information

Dear Colleagues,

The rapid and emerging surge of Internet of Things (IoT) healthcare applications has caught the attention of everyone and already knocked on the doors of almost every field. The widely spreading applications of IoT have inspired different domains, e.g., digital healthcare, bioinformatics, and cybernetics, with innovative trends and practices. In addition to providing comforts, happiness, and facilities at economic rates, there are various associated critical challenges, especially in maintaining security and privacy during sharing of secret and sensitive information in healthcare domains. In addition, the ease and fairness of resource allocation in the different intelligent platforms that IoT has brought to the modern world cannot even avoid threats, eavesdropping, and information leakage resulting from activities of hackers and attackers in the current digital healthcare landscape. Various aspects of such challenges are still unanswered, particularly in the medical field. Currently, IoT interconnects the Internet with sensors and different tiny portable devices by adopting an IP-enabled communication pattern. IoT has also played a significant role in revolutionizing the healthcare sector by providing state-of-the-art facilities, such as the remote monitoring of patients, aging and assisted living management, childcare, etc. Hence, secure and private content delivery strategies are the cornerstones of IoT application.

Most of the applications, as mentioned earlier, are highly dependent on intelligent and self-adaptive sensor-oriented entities. Sensor-based smart medical devices monitor patient health at a reasonable and efficient pace through providing correct detection and direction. The self-adaptive features of IoT-driven wearable devices empower innovative and pervasive healthcare with high-security demands to replace the conventional methods. In addition, modern security provisioning trends are more efficient in rectifying the different cyber attacks, threats, and intruders. One of the examples is compromised patient on-/in-body information during device-to-device communication from physicians to medical centers/theaters and from healthcare giving centers/nursing staff to the patients.

In establishing this Special Issue, I was inspired by the rapidly increasing security risks we all face, from wearable device manufacturers, IT professionals, and hardware/software engineers to firewall and security ensuring departments. To effectively rectify the attacks and threats in the present IoT-enabled healthcare era, this Special Issue will focus on the notion of recent advanced trends in secure, private, and trusted IoT for healthcare applications. Topics of interest include but are not limited to the following fields:

  • AI-driven methods for resource allocation in secure edge computing applications
  • Energy efficient and secure ambient assisted living
  • QoS/QoE monitoring in private and secure mobile healthcare applications
  • Secure antenna design methods for body-centric medical health
  • Trusted power-aware Bio-Nano and MEMS frameworks for Internet of Medical Things (IoMT)
  • Blockchain technologies for reliable and trustworthy computing
  • Secure narrowband IoT
  • Biometric security for medical applications
  • Physiological based data authentication protocols for health monitoring
  • Resource-constrained security solution for healthcare systems
  • Lightweight authentication and data encryption methods
  • Physical layer security for IoT
  • Blockchain enabled secure system for digital healthcare
  • Cybernetics body area network for the healthcare system
  • Fraud detection techniques for healthcare applications
  • ML as a solution and risk factor for IoT security

Dr. Ali Hassan Sodhro
Dr. Sandeep Pirbhulal
Dr. Abdullah Lakhan
Guest Editors

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Keywords

  • IoT security
  • serverless scheduling
  • fraud detection
  • digital healthcare
  • fog computing
  • cloud computing
  • biometric
  • cybernetics

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Published Papers (2 papers)

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Research

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30 pages, 1841 KiB  
Article
Dynamic Application Partitioning and Task-Scheduling Secure Schemes for Biosensor Healthcare Workload in Mobile Edge Cloud
by Abdullah Lakhan, Jin Li, Tor Morten Groenli, Ali Hassan Sodhro, Nawaz Ali Zardari, Ali Shariq Imran, Orawit Thinnukool and Pattaraporn Khuwuthyakorn
Electronics 2021, 10(22), 2797; https://doi.org/10.3390/electronics10222797 - 15 Nov 2021
Cited by 23 | Viewed by 3686
Abstract
Currently, the use of biosensor-enabled mobile healthcare workflow applications in mobile edge-cloud-enabled systems is increasing progressively. These applications are heavyweight and divided between a thin client mobile device and a thick server edge cloud for execution. Application partitioning is a mechanism in which [...] Read more.
Currently, the use of biosensor-enabled mobile healthcare workflow applications in mobile edge-cloud-enabled systems is increasing progressively. These applications are heavyweight and divided between a thin client mobile device and a thick server edge cloud for execution. Application partitioning is a mechanism in which applications are divided based on resource and energy parameters. However, existing application-partitioning schemes widely ignore security aspects for healthcare applications. This study devises a dynamic application-partitioning workload task-scheduling-secure (DAPWTS) algorithm framework that consists of different schemes, such as min-cut algorithm, searching node, energy-enabled scheduling, failure scheduling, and security schemes. The goal is to minimize the energy consumption of nodes and divide the application between local nodes and edge nodes by applying the secure min-cut algorithm. Furthermore, the study devises the secure-min-cut algorithm, which aims to migrate data between nodes in a secure form during application partitioning in the system. After partitioning the applications, the node-search algorithm searches optimally to run applications under their deadlines. The energy and failure schemes maintain the energy consumption of the nodes and the failure of the system. Simulation results show that DAPWTS outperforms existing baseline approaches by 30% in terms of energy consumption, deadline, and failure of applications in the system. Full article
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21 pages, 3141 KiB  
Review
A Systematic Review and IoMT Based Big Data Framework for COVID-19 Prevention and Detection
by Soomaiya Hamid, Narmeen Zakaria Bawany, Ali Hassan Sodhro, Abdullah Lakhan and Saleem Ahmed
Electronics 2022, 11(17), 2777; https://doi.org/10.3390/electronics11172777 - 3 Sep 2022
Cited by 21 | Viewed by 3660
Abstract
The Internet of Medical Things (IoMT) is transforming modern healthcare systems by merging technological, economical, and social opportunities and has recently gained traction in the healthcare domain. The severely contagious respiratory syndrome coronavirus called COVID-19 has emerged as a severe threat to public [...] Read more.
The Internet of Medical Things (IoMT) is transforming modern healthcare systems by merging technological, economical, and social opportunities and has recently gained traction in the healthcare domain. The severely contagious respiratory syndrome coronavirus called COVID-19 has emerged as a severe threat to public health. COVID-19 is a highly infectious virus that is spread by person-to-person contact. Therefore, minimizing physical interactions between patients and medical healthcare workers is necessary. The significance of technology and its associated potential were fully explored and proven during the outbreak of COVID-19 in all domains of human life. Healthcare systems employ all modes of technology to facilitate the increasing number of COVID-19 patients. The need for remote healthcare was reemphasized, and many remote healthcare solutions were adopted. Various IoMT-based systems were proposed and implemented to support traditional healthcare systems with reaching the maximum number of people remotely. The objective of this research is twofold. First, a systematic literature review (SLR) is conducted to critically evaluate 76 articles on IoMT systems for different medical applications, especially for COVID-19 and other health sectors. Secondly, we briefly review IoMT frameworks and the role of IoMT-based technologies in COVID-19 and propose a framework, named ‘cov-AID’, that remotely monitors and diagnoses the disease. The proposed framework encompasses the benefits of IoMT sensors and extensive data analysis and prediction. Moreover, cov-AID also helps to identify COVID-19 outbreak regions and alerts people not to visit those locations to prevent the spread of infection. The cov-AID is a promising framework for dynamic patient monitoring, patient tracking, quick disease diagnosis, remote treatment, and prevention from spreading the virus to others. We also discuss potential challenges faced in adopting and applying big data technologies to combat COVID-19. Full article
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