Abstract
Medical Cyber-Physical Systems (MCPS) hold the promise of reducing human errors and optimizing healthcare by delivering new ways to monitor, diagnose and treat patients through integrated clinical environments (ICE). Despite the benefits provided by MCPS, many of the ICE medical devices have not been designed to satisfy cybersecurity requirements and, consequently, are vulnerable to recent attacks. Nowadays, ransomware attacks account for 85% of all malware in healthcare, and more than 70% of attacks confirmed data disclosure. With the goal of improving this situation, the main contribution of this paper is an automatic, intelligent and real-time system to detect, classify, and mitigate ransomware in ICE. The proposed solution is fully integrated with the ICE++ architecture, our previous work, and makes use of Machine Learning (ML) techniques to detect and classify the spreading phase of ransomware attacks affecting ICE. Additionally, Network Function Virtualization (NFV) and Software Defined Networking (SDN)paradigms are considered to mitigate the ransomware spreading by isolating and replacing infected devices. Different experiments returned a precision/recall of 92.32%/99.97% in anomaly detection, an accuracy of 99.99% in ransomware classification, and promising detection and mitigation times. Finally, different labelled ransomware datasets in ICE have been created and made publicly available.
Highlights
The increasing resilience to antibiotics, an ageing population, the epidemic obesity, or the impact of pollution are factors that increase the difficult for hospitals and care centres to effectively care for patients globally
Additional experiments demonstrated the viability of the proposed solution in terms of time
Monitoring: Generating Network Flow Features in integrated clinical environments (ICE). This is the first module of our system and focuses on monitoring in real time and continuously network packets exchanged between the medical devices and databases of ICE
Summary
The increasing resilience to antibiotics, an ageing population, the epidemic obesity, or the impact of pollution are factors that increase the difficult for hospitals and care centres to effectively care for patients globally. Hospitals are constantly incorporating technological innovations to face these aspects and improve the quality of the healthcare provided within their borders in the hospital rooms of the future In this context, new paradigms such as the Internet of Medical Things (IoMT) [1], and Medical. MCPS refer to safety-critical interconnected medical systems that analyse patients’ vital signs gathered from medical devices, infer the state of the patient’s health, and initiate treatments issuing information to doctors or directly to medical actuators. This disruptive vision has the potential to enable in a cost-efficient way the next-generation of healthcare, which requires systems able to interoperate efficiently, safely, and securely [3]. The use of interconnected patient-centric medical devices in operating rooms or intensive care units will contribute to reduce human errors and optimize healthcare treatments
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