A Survey on Security and Privacy Issues in Modern Healthcare Systems: Attacks and Defenses
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Abstract (arXiv)
The recent advancements in computing systems and wireless communications have made healthcare systems more efficient than before. Modern healthcare devices can monitor and manage different health conditions of the patients automatically without any manual intervention from medical professionals. Additionally, the use of implantable medical devices (IMDs), body area networks (BANs), and Internet of Things (IoT) technologies in healthcare systems improve the overall patient monitoring and treatment process. However, these systems are complex in software and hardware, and optimizing between security, privacy, and treatment is crucial for healthcare systems as any security or privacy violation can lead to severe effects on patients' treatments and overall health conditions. Indeed, the healthcare domain is increasingly facing security challenges and threats due to numerous design flaws and the lack of proper security measures in healthcare devices and applications. In this paper, we explore various security and privacy threats to healthcare systems and discuss the consequences of these threats. We present a detailed survey of different potential attacks and discuss their impacts. Furthermore, we review the existing security measures proposed for healthcare systems and discuss their limitations. Finally, we conclude the paper with future research directions toward securing healthcare systems against common vulnerabilities.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 May 2020.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 2; 2025: 3.
7 papers.
- 2025Cyber-Physical Systems Security: A Comprehensive Review of Anomaly Detection Techniquescited by 4
- 2022Survey of Machine Learning Based Intrusion Detection Methods for Internet of Medical Thingscited by 2
- 2023MLHOps: Machine Learning for Healthcare Operationscited by 2
- 2024Federated Hybrid Training and Self-Adversarial Distillation: Towards Robust Edge Networkscited by 2
- 2024Medical Image Data Provenance for Medical Cyber-Physical Systemcited by 1
- 2025Explainable AI for Securing Healthcare in IoT-Integrated 6G Wireless Networkscited by 0
- 2025Federated Data Analytics for Cancer Immunotherapy: A Privacy-Preserving Collaborative Platform for Patient Managementcited by 0
- 2025Federated Data Analytics for Cancer Immunotherapy: A Privacy-Preserving Collaborative Platform for Patient Management10 Oct 2025
- 2025Explainable AI for Securing Healthcare in IoT-Integrated 6G Wireless Networks20 May 2025
- 2025Cyber-Physical Systems Security: A Comprehensive Review of Anomaly Detection Techniques18 Feb 2025
- 2024Federated Hybrid Training and Self-Adversarial Distillation: Towards Robust Edge Networks26 Dec 2024
- 2024Medical Image Data Provenance for Medical Cyber-Physical System22 Mar 2024
- 2023MLHOps: Machine Learning for Healthcare Operations4 May 2023
- 2022Survey of Machine Learning Based Intrusion Detection Methods for Internet of Medical Things19 Feb 2022