Clinicians' Perspectives on Healthcare Cybersecurity and Cyber Threats

INTRODUCTION

In today's world, healthcare systems face various risks, including data breaches, theft, and damage. This is where cybersecurity comes in, as it helps protect sensitive personal and financial data, such as electronic health records. This study delved into the perspectives of clinicians on cybersecurity in healthcare, exploring how it impacts patient safety and the functioning of organizations. The study also identified challenges associated with implementing cybersecurity measures and the risks of not doing so.

METHOD

This is a qualitative study in which clinical informaticians from different health science backgrounds were asked to share their opinions using the Delphi technique, with 48 participants engaging in all three rounds.

RESULTS

The study highlighted that 96% of participants deemed cybersecurity in healthcare critical for protecting data. Compliance with regulations (91.7%), reduced disruptions (69%), improved patient care (65%), trust (58.3%), and reputation (54%) were additional advantages. However, the study also identified top challenges to cybersecurity implementation, such as time/resource constraints (65%) and disruption to workflows/services (60.4%). Staff resistance, insider threats, and legacy system issues were also anticipated obstacles. Neglecting to implement cybersecurity measures in healthcare could lead to a higher risk of data breaches (96%), financial/legal penalties for hospitals (79%), and concerns about patient safety (65%).

CONCLUSION

It is imperative to prioritize cybersecurity in the healthcare industry to mitigate these risks and ensure patient confidence, health system stability, and, ultimately, save lives. A unified approach is required to enforce policies, modify behaviors, and adopt innovative practices to combat cyberattacks effectively.

Predicting Cybersecurity Threats in Critical Infrastructure for Industry 4.0: A Proactive Approach Based on Attacker Motivations

In Industry 4.0, manufacturing and critical systems require high levels of flexibility and resilience for dynamic outcomes. Industrial Control Systems (ICS), specifically Supervisory Control and Data Acquisition (SCADA) systems, are commonly used for operation and control of Critical Infrastructure (CI). However, due to the lack of security controls, standards, and proactive security measures in the design of these systems, they have security risks and vulnerabilities. Therefore, efficient and effective security solutions are needed to secure the conjunction between CI and I4.0 applications. This paper predicts potential cyberattacks and threats against CI systems by considering attacker motivations and using machine learning models. The approach presents a novel cybersecurity prediction technique that forecasts potential attack methods, depending on specific CI and attacker motivations. The proposed model's accuracy in terms of False Positive Rate (FPR) reached 66% with the trained and test datasets. This proactive approach predicts potential attack methods based on specific CI and attacker motivations, and doubling the trained data sets will improve the accuracy of the proposed model in the future.