3 papers
cs.CR2026
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices
Mohammadreza Hallajiyan, Xueren Ge, Athish Pranav Dharmalingam +4
The growing integration of artificial intelligence (AI) and machine learning (ML) in medical systems requires effective measures to address emerging security risks. One such risk i…
cs.CR2025
Systems-Theoretic and Data-Driven Security Analysis in ML-enabled Medical Devices
Gargi Mitra, Mohammadreza Hallajiyan, Inji Kim +5
The integration of AI/ML into medical devices is rapidly transforming healthcare by enhancing diagnostic and treatment facilities. However, this advancement also introduces serious…
cs.CR2024
Systematically Assessing the Security Risks of AI/ML-enabled Connected Healthcare Systems
Mohammed Elnawawy, Mohammadreza Hallajiyan, Gargi Mitra +2
The adoption of machine-learning-enabled systems in the healthcare domain is on the rise. While the use of ML in healthcare has several benefits, it also expands the threat surface…