Healthcare_Vulnerabilities_2025
Description
This dataset contains information about cybersecurity vulnerabilities affecting healthcare systems. The data is structured according to the Common Vulnerabilities and Exposures (CVE) standard and includes details such as vulnerability identifiers, descriptions, severity levels, CVSS scores, and publication dates. The dataset is designed to support cybersecurity research, vulnerability assessment, and risk analysis in healthcare infrastructure. The dataset focuses on identifying high-severity vulnerabilities that may potentially be exploited as zero-day attacks, enabling researchers to study threat patterns and develop defensive mechanisms. Each entry represents a vulnerability instance that may impact healthcare software, medical devices, or healthcare information systems. The vulnerability severity is measured using the Common Vulnerability Scoring System (CVSS), which provides a standardized way to assess the potential impact of security vulnerabilities. The dataset can be used for tasks such as vulnerability prioritization, risk assessment, anomaly detection research, and security model development.
Files
Steps to reproduce
The dataset was generated using vulnerability data from the National Vulnerability Database (NVD), which is a publicly available database maintained by the National Institute of Standards and Technology. First, a Python script was used to access the NVD API and retrieve vulnerability records using healthcare-related keywords such as healthcare, medical device, hospital, patient monitor, and electronic health record (EHR). The script collected vulnerability information including CVE ID, description, CVSS score, severity level, attack vector, attack complexity, and published date. Next, the raw data was stored in a CSV dataset and data preprocessing techniques were applied to improve data quality. During preprocessing, unnecessary columns such as attack vector and attack complexity were removed, duplicate entries were eliminated, and rows containing missing values were deleted. The dataset was then cleaned and standardized for analysis. Finally, the cleaned dataset was filtered to include only vulnerabilities belonging to the year 2025.
Institutions
- CT Group Of InstitutionsPunjab, Jalandhar