A Highly Scalable Automated Universal Binary Malware Analysis Framework for Healthcare and Medical SaaS

A Highly Scalable Automated Universal Binary Malware Analysis Framework for Healthcare and Medical SaaS

연구 분야: Safety

학회: ICMHI '24: Proceedings of the 2024 8th International Conference on Medical and Health Informatics

In recent years, there has been a growing emphasis on information security, with major companies introducing cybersecurity teams to ensure the safety of data. However, there is a lack of convenient channels for general users to engage in cybersecurity protection, leaving them with no choice but to rely on various antivirus software installations to safeguard their privacy and financial assets. This phenomenon is particularly evident in the digital transformation of healthcare and medical information systems, where the substantial amount of digitized patient data has become a crucial asset within hospital systems. Unfortunately, it has also made healthcare systems potential targets for cyberattacks. The databases of major hospitals have become vulnerable to malicious virus invasions, posing significant threats to patient privacy and the operational integrity of healthcare institutions. Faced with such threats, there is an increasing need for comprehensive cybersecurity protection mechanisms. To address this issue, we have developed the Universal Binary Malware Analysis Framework (UBMAF), an easily accessible binary file analysis framework for the general public. UBMAF integrates multiple open-source static and dynamic analysis tools into an automated module, deployed as Software as a Service (SaaS) in the cloud for healthcare and medical systems. This eliminates the need for users to install applications, and the framework interface is optimized for intuitive usability. During the usage process, users can freely choose module combinations. After uploading files to UBMAF, the framework conducts corresponding tool analyses or file processing based on the selected modules. Ultimately, it provides users with downloadable results and analysis reports. This design enables large healthcare and medical systems to quickly and conveniently enhance their cybersecurity defenses while ensuring the security of digital medical data, effectively addressing the challenges brought about by the digital transformation of healthcare.