Comparing the Use of EMBA for IoT Firmware Security Analysis on Cloud Services and Standalone Servers

This study presents a quantitative evaluation of the EMBA firmware security analysis tool applied to Internet of Things (IoT) and embedded device firmware in two deployment environments: a standalone personal computer and a Microsoft Azure cloud-based virtual machine. The study addresses a gap in existing research regarding how deployment choices affect performance, cost, and operational characteristics of firmware security analysis. Using identical EMBA configurations and analysis modules, firmware images of varying sizes were analyzed, while execution time, detected vulnerabilities, and resource utilization were systematically recorded. The results demonstrate that scan duration is influenced by both firmware size and deployment environment. Specifically, using EMBA v1.5.0, a 25.5 MB firmware image required approximately 14 hours on a standalone system and over 25 hours on Azure Cloud, whereas a 30.2 MB image completed in approximately 18 hours locally and 17 hours on Azure Cloud. Despite these differences in execution time, the type and number of identified vulnerabilities were largely consistent across both environments, indicating comparable analytical coverage. A cost assessment shows that cloud-based execution incurred approximately US $250 for a limited set of analyses, while standalone deployment required higher initial investment but provided predictable long-term costs. Overall, this deployment-focused evaluation offers empirical information into performance, cost, and operational trade-offs, supporting informed decision-making for IoT security practitioners selecting local or cloud-based firmware analysis environments.