An In-Depth Study of Smart Building Systems: Firmware Analysis and Device Emulation

The Internet of Things (IoT) devices have become crucial components in modern systems, serving a diverse range of functions, including environmental monitoring, device management, and creating networks for communications. As the proliferation of intelligent devices extends across various domains, from residential settings to vehicles, it is crucial to comprehensively understand their operational workflows. In particular, assessing their security has emerged as a foremost concern. There are several approaches to understanding the behavior of software, ranging from static analysis to more advanced techniques, such as symbolic and concolic analysis. However, the most effective method for gaining an in-depth understanding of a device's operations is dynamic analysis. This approach allows for a realistic simulation of the device, providing results that closely reflect real-world performance and enabling the examination of a broader range of code. This thesis aims to explore the realm of Smart Buildings by investigating the operation of Building Management Systems (BMS) and the devices integrated within these systems. A significant gap in the current body of research concerning Smart Buildings is the limited availability of datasets used for experimentation. To address this gap, this work contributes by creating a comprehensive database containing over 50 firmware samples from leading vendors in the sector. Using this curated pool of firmware, analyses were conducted with the EMBA tool, which facilitates the examination of software functionality. Additionally, efforts were made to establish an environment for device emulation, enabling more accurate and scalable experimentation.