Cyber Threats in E-healthcare and an Autonomous Cybersecurity Agent: A Comprehensive Review
DOI:
https://doi.org/10.47852/bonviewAIA62029545Keywords:
E-healthcare, cyberattacks, autonomous security agent, privacy, secrecyAbstract
In the future, an AI-driven security agent could be designed to face cyberattacks for small-scale E-healthcare systems. With the evolution of the Internet, E-healthcare information is made available within seconds on any electronic device, irrespective of the user’s geographical location. Since E-healthcare information can be accessed flexibly by individuals on the Internet, as such these are prone to cyberattacks by hackers and even the critical healthcare infrastructure. This study is a critical narrative review of the threats faced by the E-healthcare sector while proposing autonomous AI-driven security agents for improving cyber resilience. The major attacks faced by the E-healthcare systems are ransomware, phishing, data breaches, malware, Distributed Denial of Service, Structured Query Language injection, and Man-in-the-Middle, together with their influence on privacy, confidentiality, authenticity, and patient safety. In this article, a seven-stage cybersecurity response framework consisting of identification, protection, detection, response, recovery, procurement, and security audit is introduced. This architecture is capable of sensing, analyzing, responding to, and learning from the changing attack patterns to ensure security from future attacks. This article also highlights the significance of AI-assisted security mechanisms, staff awareness, and privacy-preserving practices in enhancing defenses of the electronic healthcare sector. In the future, the proposed framework could be implemented and validated as eventually cybersecurity needs to be adaptive to cyberattacks.
Received: 6 March 2026 | Revised: 25 June 2026 | Accepted: 2 July 2026
Conflicts of Interest
The authors declare that they have no conflicts of interest to this work.
Data Availability Statement
Data sharing is not applicable to this article as no new data were created or analyzed in this study.
Author Contribution Statement
Divya Sharma: Conceptualization, Methodology, Software, Formal analysis, Resources, Data curation, Writing – original draft, Visualization. Chander Prabha: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Writing – review & editing, Supervision, Project administration. Amna Bamaqa: Software, Investigation, Resources, Data curation. Wedad O. Alahamade: Formal analysis, Investigation, Resources, Data curation, Writing – review & editing, Visualization. Mohammad Zubair Khan: Validation, Supervision, Project administration.
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This work is licensed under a Creative Commons Attribution 4.0 International License.
