Aidynov T., Tleuberdin S., Nurusheva A., Satybaldina D., Altaibek M., Boranbay Z.
Cross-layer security assessment in IoT ecosystems: analyzing vulnerabilities in the Zigbee protocol // Proceedings of the 2025 IEEE European Technology and Engineering Management Summit (E-TEMS). — 2025. — Conference held 26–28 May 2025. — DOI: 10.1109/E-TEMS64751.2025.11239104.

Abstract: The increasing integration of IoT devices in smart home environments introduces significant security concerns, particularly in communication protocols such as Zigbee. This paper proposes a conceptual cross-layer security assessment model targeting vulnerabilities across firmware, network traffic, and user behavior. The study focuses on the implementation and evaluation of the network traffic analysis component. Using the UNSW-NB15 dataset, a Random Forest-based anomaly detection method is validated and demonstrates strong performance in identifying suspicious traffic patterns, including potential Zigbee-related attacks. Additional components, such as firmware analysis through entropy and API call extraction, and user behavior modeling using graph neural networks, are outlined for future development. The results highlight the effectiveness of traffic-based detection and establish a foundation for comprehensive, multi-layered security analysis in resource-constrained IoT systems.

Link / DOI: https://doi.org/10.1109/E-TEMS64751.2025.11239104