Ransomware Detection in Healthcare: Enhancing Cybersecurity with Processor and Disk Usage Data

Rongali Abhiram, Kunal, J. Shobana

2025

Abstract

Security of sensitive medical information and critical patient care is threatened with the increasing digitization of healthcare infrastructure, making hospitals prime targets for ransomware attacks. Besides having a significant computational burden, conventional detection methods such as signature-based and behavioural analysis are often lagging the rapidly evolving ransomware variants. This paper presents a new approach to detecting ransomware through host machine-level processor and disk I/O event monitoring and is tailored for use in healthcare environments. With the use of an RF classifier and machine learning-based method, the solution can detect threats in real time without affecting system performance. The framework is rigorously tested under simulated hospital workload scenarios and 22 ransomware variants, demonstrating its robustness, effectiveness, and adaptability to safeguard healthcare infrastructures from modern ransomware attacks.

Paper Citation

in Harvard Style

Abhiram R., Kunal. and Shobana J. (2025). Ransomware Detection in Healthcare: Enhancing Cybersecurity with Processor and Disk Usage Data. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 188-193. DOI: 10.5220/0013910000004919

in Bibtex Style

@conference{icrdicct`2525,
author={Rongali Abhiram and Kunal and J. Shobana},
title={Ransomware Detection in Healthcare: Enhancing Cybersecurity with Processor and Disk Usage Data},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={188-193},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013910000004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Ransomware Detection in Healthcare: Enhancing Cybersecurity with Processor and Disk Usage Data
SN - 978-989-758-777-1
AU - Abhiram R.
AU - Kunal.
AU - Shobana J.
PY - 2025
SP - 188
EP - 193
DO - 10.5220/0013910000004919
PB - SciTePress