Threat to trust: A systematic review on Internet of medical things security

The Internet of Medical Things (IoMT) has transformed healthcare by enabling seamless communication among medical devices, supporting real-time monitoring, diagnostics, vital patient data tracking, improved patient care, disease prediction, early warning, and enhanced operational efficiency. Due to...

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Veröffentlicht in:Journal of parallel and distributed computing Jg. 206; S. 105172
Hauptverfasser: Shammar, Elham, Cui, Xiaohui, Zahary, Ammar, Alsamhi, Saeed Hamood, Al-qaness, Mohammed A.A.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Inc 01.12.2025
Schlagworte:
Attack
Blockchain
Decentralized healthcare
IoMT
Machine learning
Parallel and distributed computing
Security and privacy
Parallel and distributed computing
Security and privacy
Blockchain
Machine learning
Attack
Decentralized healthcare
IoMT
ISSN:0743-7315
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Abstract The Internet of Medical Things (IoMT) has transformed healthcare by enabling seamless communication among medical devices, supporting real-time monitoring, diagnostics, vital patient data tracking, improved patient care, disease prediction, early warning, and enhanced operational efficiency. Due to the sensitive nature of health-related data, the adoption of IoMT has raised significant privacy and security concerns, prompting comprehensive evaluation of IoMT security and making it a prime target for cyberattacks such as ransomware, denial-of-service (DoS) attacks, and malware. Securing IoMT requires efficient data processing across distributed systems to ensure both confidentiality and availability. Parallel and distributed computing can address scalability and performance challenges in IoMT security, particularly in enabling real-time monitoring and threat detection across multiple interconnected devices. This survey conducts a systematic literature review (SLR) of IoMT security to analyze key issues, categorize security threats, attack vectors, and vulnerabilities, and examine how emerging technologies such as blockchain, machine learning (ML), and physically unclonable functions (PUF) are strengthening IoMT security. This SLR reviews IoMT security research published between 2020 and 2024 to identify challenges and provide insights for future researchers and developers of new IoMT security models. This SLR offers practitioners and researchers guidance for developing reliable and resilient IoMT security systems in the decentralized healthcare industry. •A comprehensive overview of IoMT security, addressing issues, attacks, threats, and challenges.•Review the latest IoMT security research published between 2020 and 2024.•Highlight the limitations of current IoMT security research and propose potential solutions.•Providing a clear roadmap for future research and development in IoMT security.•Provide a structured approach for academics to investigate emerging gaps in IoMT security research.
AbstractList The Internet of Medical Things (IoMT) has transformed healthcare by enabling seamless communication among medical devices, supporting real-time monitoring, diagnostics, vital patient data tracking, improved patient care, disease prediction, early warning, and enhanced operational efficiency. Due to the sensitive nature of health-related data, the adoption of IoMT has raised significant privacy and security concerns, prompting comprehensive evaluation of IoMT security and making it a prime target for cyberattacks such as ransomware, denial-of-service (DoS) attacks, and malware. Securing IoMT requires efficient data processing across distributed systems to ensure both confidentiality and availability. Parallel and distributed computing can address scalability and performance challenges in IoMT security, particularly in enabling real-time monitoring and threat detection across multiple interconnected devices. This survey conducts a systematic literature review (SLR) of IoMT security to analyze key issues, categorize security threats, attack vectors, and vulnerabilities, and examine how emerging technologies such as blockchain, machine learning (ML), and physically unclonable functions (PUF) are strengthening IoMT security. This SLR reviews IoMT security research published between 2020 and 2024 to identify challenges and provide insights for future researchers and developers of new IoMT security models. This SLR offers practitioners and researchers guidance for developing reliable and resilient IoMT security systems in the decentralized healthcare industry. •A comprehensive overview of IoMT security, addressing issues, attacks, threats, and challenges.•Review the latest IoMT security research published between 2020 and 2024.•Highlight the limitations of current IoMT security research and propose potential solutions.•Providing a clear roadmap for future research and development in IoMT security.•Provide a structured approach for academics to investigate emerging gaps in IoMT security research.
ArticleNumber 105172
Author Cui, Xiaohui
Shammar, Elham
Alsamhi, Saeed Hamood
Al-qaness, Mohammed A.A.
Zahary, Ammar
Author_xml – sequence: 1
  givenname: Elham
  orcidid: 0000-0003-3493-1025
  surname: Shammar
  fullname: Shammar, Elham
  email: eshammar@whu.edu.cn
  organization: Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, China
– sequence: 2
  givenname: Xiaohui
  surname: Cui
  fullname: Cui, Xiaohui
  email: xcui@whu.edu.cn
  organization: Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, China
– sequence: 3
  givenname: Ammar
  surname: Zahary
  fullname: Zahary, Ammar
  email: zahary@su.edu.ye
  organization: Department of Information Technology, Faculty of Computer and Information Technology (FCIT), Sana'a University, Sana'a 1247, Yemen
– sequence: 4
  givenname: Saeed Hamood
  surname: Alsamhi
  fullname: Alsamhi, Saeed Hamood
  email: saeed.alsamhi@insight-centre.org
  organization: Insight Centre for Data Analytics, University of Galway, Ireland
– sequence: 5
  givenname: Mohammed A.A.
  surname: Al-qaness
  fullname: Al-qaness, Mohammed A.A.
  email: alqaness@zjnu.edu.cn
  organization: College of Physics and Electronic Information Engineering, Zhejiang Normal University, Jinhua 321004, China
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Keywords Parallel and distributed computing
Security and privacy
Blockchain
Machine learning
Attack
Decentralized healthcare
IoMT
Language English
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Snippet The Internet of Medical Things (IoMT) has transformed healthcare by enabling seamless communication among medical devices, supporting real-time monitoring,...
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StartPage 105172
SubjectTerms Attack
Blockchain
Decentralized healthcare
IoMT
Machine learning
Parallel and distributed computing
Security and privacy
Title Threat to trust: A systematic review on Internet of medical things security
URI https://dx.doi.org/10.1016/j.jpdc.2025.105172
Volume 206
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