The number of cyber-attacks around the world exploded in 2020: exploiting the Covid-19 pandemic as an opportunity for cybercriminals to take advantage of the shift in focus towards smart working and hospital staff transferred to the frontline.
This paper (February 2018) modelled the level of exposure, security and organisational factors associated with healthcare data breaches.
Abstract: The number of healthcare data breaches continues to increase at an alarming rate. The purpose of this study was to develop a model of factors associated with healthcare data breaches. Variables were operationalised as the healthcare facilities' level of exposure, level of security, and organisational factors. The outcome variable was the binary value for data breach/no data breach. Because healthcare data breaches carry the risk of personal health information exposure, corruption or destruction, this study is important to the healthcare field.
Binary logistic regression was utilised to examine a representative data breach model. Results indicate several exposure, security and organisational factors significantly associated with healthcare data breaches.
Data sources: Department of Health and Human Services database of healthcare facilities reporting data breaches and from a large national database of technical and organisational infrastructure information. Binary logistic regression was utilized to examine a representative data breach model. Results indicate several exposure, security and organizational factors significantly associated with healthcare data breaches.
Results: Healthcare data breaches risk exposing personal health information making this study important to the healthcare field.
Decision Support Systems Volume 108, April 2018, Pages 57-68
PANACEA Research perspectives: This paper is of general interest to PANACEA as part of its holistic approach to cybersecurity in healthcare, including risk and threat modelling.
Keywords: Cyber security, Cyber risk, Data breach, Risk management, Exposure Vulnerability assessment, Exposure Level, Security modeling, Cyber-analytics
Lookout Watch entry date: 07/08/2019