Secure and Privacy-Preserving Smart Healthcare

A special issue of Healthcare (ISSN 2227-9032). This special issue belongs to the section "Healthcare Quality and Patient Safety".

Deadline for manuscript submissions: closed (5 April 2023) | Viewed by 11926

Special Issue Editors


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Guest Editor
School of Information Security and Applied Computing, College of Engineering & Technology, Eastern Michigan University, Ypsilanti, MI 48197, USA
Interests: microelectronics/hardware assisted security; emerging IoT and connected autonomous systems security; security and privacy of smart building and spaces in modern smart cities environment; trusted next generations smart power grid networks
Special Issues, Collections and Topics in MDPI journals
School of Computing and IT Lakeside Campus, Taylors University, Subang Jaya, Selangor, Malaysia
Interests: cybersecurity; Internet of Things; WSN; Smart Cities; IoT
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Computer Engineering and Information Security, International Information Technology University, Almaty, Kazakhstan
Interests: artificial intelligence; cryptographic algorithms; cryptocurrency; cyber physical system; cyber vulnerabilities, threat and control; data mining; deep learning; energy preservation; fog computing; image processing; intelligent transportation system; internet-of-things; Li-Fi; machine learning; signal processing; supervised, unsupervised; semi supervised learning

Special Issue Information

Dear Colleagues,

Smart healthcare technologies are becoming more and more profoundly and ubiquitously integrated in the fabric of wearable and implantable devices used to monitor and diagnose a wide range of medical conditions to enhance our lifestyles and save lives. Unfortunately, smart healthcare applications are progressively incorporated into untrusted and insecure physical environments, and thus they are significantly vulnerable to new cyber- and physical-system attackers. Standard security techniques may not suit extreme innovative healthcare applications requiring high performance (low power, small area overhead, etc.) and competing for computational and robust security solutions. Therefore, with these security challenges, the next generation of intelligent healthcare technology will need to be protected and trusted to provide life-critical roles, relying on robust security mechanisms before launching spontaneous or combined cyber-attacks.

This Special Issue calls for novel and state-of-the-art solutions to enable trust in innovative healthcare applications and propose new efficient security solutions for wearable and implantable medical devices. For that, the issue seeks papers with a proposed secure and privacy-preserving solution that constructs imminent healthcare applications against the emerging cyber and physical attacks without significantly degrading system performance.

Dr. Fathi Amsaad
Dr. Noor Zaman
Dr. Razaque Abdul
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. Healthcare 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 2700 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

  • wireless sensor network (WSN) for secure smart healthcare
  • security and privacy of internet of medical things (IoMT) applications
  • mobile and edge computing for security and privacy of smart healthcare
  • hardware-assisted security for trusted healthcare systems
  • privacy-preserving blockchain-enabled schemes for secure Smart Healthcare
  • AI-enabled approaches for secure IoT-based medical applications
  • secure ad hoc-based and internet of medical networks
  • big data privacy-preserving models
  • cloud computing for secure and private big medical data
  • lightweight cryptography for secure medical devices
  • federated and machine learning techniques for IoMT security

Published Papers (3 papers)

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Research

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18 pages, 1837 KiB  
Article
Use Case Evaluation and Digital Workflow of Breast Cancer Care by Artificial Intelligence and Blockchain Technology Application
by Sebastian Griewing, Michael Lingenfelder, Uwe Wagner and Niklas Gremke
Healthcare 2022, 10(10), 2100; https://0-doi-org.brum.beds.ac.uk/10.3390/healthcare10102100 - 20 Oct 2022
Cited by 4 | Viewed by 1680
Abstract
This study aims at evaluating the use case potential of breast cancer care for artificial intelligence and blockchain technology application based on the patient data analysis at Marburg University Hospital and, thereupon, developing a digital workflow for breast cancer care. It is based [...] Read more.
This study aims at evaluating the use case potential of breast cancer care for artificial intelligence and blockchain technology application based on the patient data analysis at Marburg University Hospital and, thereupon, developing a digital workflow for breast cancer care. It is based on a retrospective descriptive data analysis of all in-patient breast and ovarian cancer patients admitted at the Department of Gynecology of Marburg University Hospital within the five-year observation period of 2017 to 2021. According to the German breast cancer guideline, the care workflow was visualized and, thereon, the digital concept was developed, premised on the literature foundation provided by a Boolean combination open search. Breast cancer cases display a lower average patient case complexity, fewer secondary diagnoses, and performed procedures than ovarian cancer. Moreover, 96% of all breast cancer patients originate from a city with direct geographical proximity. Estimated circumference and total catchment area of ovarian present 28.6% and 40% larger, respectively, than for breast cancer. The data support invasive breast cancer as a preferred use case for digitization. The digital workflow based on combined application of artificial intelligence as well as blockchain or distributed ledger technology demonstrates potential in tackling senological care pain points and leveraging patient data safety and sovereignty. Full article
(This article belongs to the Special Issue Secure and Privacy-Preserving Smart Healthcare)
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27 pages, 2435 KiB  
Article
Incentive EMR Sharing System Based on Consortium Blockchain and IPFS
by Wanbing Zhan, Chin-Ling Chen, Wei Weng, Woei-Jiunn Tsaur, Zi-Yi Lim and Yong-Yuan Deng
Healthcare 2022, 10(10), 1840; https://0-doi-org.brum.beds.ac.uk/10.3390/healthcare10101840 - 22 Sep 2022
Cited by 6 | Viewed by 2109
Abstract
Electronic medical records (EMRs) are extremely private data in the medical industry. Clinicians use the patient data that the EMR stores to quickly assess a patient’s status and save diagnostic information. In the conventional medical model, it is easy for duplicate exams, medical [...] Read more.
Electronic medical records (EMRs) are extremely private data in the medical industry. Clinicians use the patient data that the EMR stores to quickly assess a patient’s status and save diagnostic information. In the conventional medical model, it is easy for duplicate exams, medical resource waste, or the loss of medical records to happen when a patient is transferred between several medical facilities due to problems with data sharing and exchange, inadequate data privacy, security, confidentiality, and difficulties with data traceability. This paper recommends a Hyperledger Fabric-based strategy to promote the exchange of EMR models. With the use of Hyperledger Fabric, EMR stakeholders can be brought into the channel to facilitate data sharing. Attribute-based access control (ABAC) allows users to design the data access control policy, and the data access control may improve security. Any record stored in the blockchain can be viewed using the Hyperledger Fabric feature and it cannot be altered or destroyed, ensuring data traceability. Through proxy re-encryption, which makes sure that the data is not leaked during data exchange, data secrecy can be ensured. A module for medical tokens has now been added. Many foreign medical institutions currently use the medical token system, and the system described in this paper can use the tokens to pay for some medical expenses. The tokens are obtained by the patient’s initiative to share their EMR with the medical institution for research, which is how many foreign medical institutions currently use the medical token mechanism. This paradigm can encourage the growth of medical data by enabling stakeholders to collaborate and share EMR trust. Full article
(This article belongs to the Special Issue Secure and Privacy-Preserving Smart Healthcare)
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Review

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32 pages, 6073 KiB  
Review
AI-Powered Blockchain Technology for Public Health: A Contemporary Review, Open Challenges, and Future Research Directions
by Ritik Kumar, Arjunaditya, Divyangi Singh, Kathiravan Srinivasan and Yuh-Chung Hu
Healthcare 2023, 11(1), 81; https://0-doi-org.brum.beds.ac.uk/10.3390/healthcare11010081 - 27 Dec 2022
Cited by 12 | Viewed by 7290
Abstract
Blockchain technology has been growing at a substantial growth rate over the last decade. Introduced as the backbone of cryptocurrencies such as Bitcoin, it soon found its application in other fields because of its security and privacy features. Blockchain has been used in [...] Read more.
Blockchain technology has been growing at a substantial growth rate over the last decade. Introduced as the backbone of cryptocurrencies such as Bitcoin, it soon found its application in other fields because of its security and privacy features. Blockchain has been used in the healthcare industry for several purposes including secure data logging, transactions, and maintenance using smart contracts. Great work has been carried out to make blockchain smart, with the integration of Artificial Intelligence (AI) to combine the best features of the two technologies. This review incorporates the conceptual and functional aspects of the individual technologies and innovations in the domains of blockchain and artificial intelligence and lays down a strong foundational understanding of the domains individually and also rigorously discusses the various ways AI has been used along with blockchain to power the healthcare industry including areas of great importance such as electronic health record (EHR) management, distant-patient monitoring and telemedicine, genomics, drug research, and testing, specialized imaging and outbreak prediction. It compiles various algorithms from supervised and unsupervised machine learning problems along with deep learning algorithms such as convolutional/recurrent neural networks and numerous platforms currently being used in AI-powered blockchain systems and discusses their applications. The review also presents the challenges still faced by these systems which they inherit from the AI and blockchain algorithms used at the core of them and the scope of future work. Full article
(This article belongs to the Special Issue Secure and Privacy-Preserving Smart Healthcare)
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