The smart home platform integrates with Internet of Things (IoT) devices, smartphones, and cloud servers, enabling seamless and convenient services. It gathers and manages extensive user data, including personal information, device operations, and patterns of user behavior. Such data plays an essential role in criminal investigations, highlighting the growing importance of specialized smart home forensics. Given the rapid advancement in smart home software and hardware technologies, many companies are introducing new devices and services that expand the market. Consequently, scalable and platform-specific forensic research is necessary to support efficient digital investigations across diverse smart home ecosystems. This study thoroughly examines the core components and structures of smart homes, proposing a generalized architecture that represents various operational environments. A three-stage smart home forensics framework is introduced: (1) analyzing application functions to infer relevant data, (2) extracting and processing data from interconnected devices, and (3) identifying data valuable for investigative purposes. The framework’s applicability is validated using testbeds from Samsung SmartThings and Xiaomi Mi Home platforms, offering practical insights for real-world forensic applications. The results demonstrate that the proposed forensic framework effectively acquires and classifies relevant digital evidence in smart home platforms, confirming its practical applicability in smart home forensic investigations.
