Abstract
Millions of intelligent terminals are connected in the IoT (Internet of Things) networks providing services for industrial applications around the world. The distributed deployment of terminals increases the exposure to cyber attackers. The detection of intelligent IoT terminals is the prerequisite for effective terminal security protections. Traditional detection methods have shortcomings such as low accuracy and difficult to detect heterogeneous terminals. Hence, a detection system for intelligent IoT terminals from the aspect of information security is proposed in this paper. Critical methods in the proposed system including comprehensive detection model and IoT protocol analysis method are studied. The system architecture including functional modules is introduced. The proposed system may operate in terminal mode and access point mode and work flows of both modes are described. Finally, the IoT terminal security is discussed from the levels of system security hardware, terminal file system and IoT network security. The proposed system is expected to detect terminals including hidden terminals in the networks of targeted area so as to effectively monitor and protect the terminals in target area.
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References
Hwang, J., Nkenyereye, L., Sung, N., Kim, J., Song, J.: IoT service slicing and task offloading for edge computing. IEEE Internet Things J. 8(14), 11526–11547 (2021)
Mo, Y., **ng, L., Guo, W., Cai, S., Zhang, Z., Jiang, J.: Reliability analysis of IoT networks with community structures. IEEE Trans. Netw. Sci. Eng. 7(1), 304–315 (2020)
Iqbal, W., Abbas, H., Daneshmand, M., Rauf, B., Bangash, Y.A.: An in-depth analysis of IoT security requirements, challenges, and their countermeasures via software-defined security. IEEE Internet Things J. 7(10), 10250–10276 (2020)
Zhu, X., Li, Q., Chen, Z., Zhang, G., Shan, P.: Research on security detection technology for internet of things terminal based on firmware code genes. IEEE Access 8, 150226–150241 (2020)
Zhu, X., Li, Q., Zhang, P., Chen, Z.: A firmware code gene extraction technology for IoT terminal. IEEE Access 7, 179591–179604 (2019)
Wu, K., Li, J., Zhang, B.: Abnormal detection of wireless power terminals in untrusted environment based on double hidden Markov model. IEEE Access 9, 18682–18691 (2021)
He, X., Yang, Y., Zhou, W., Wang, W., Liu, P., Zhang, Y.: Fingerprinting mainstream IoT platforms using traffic analysis. IEEE Internet Things J. 9(3), 2083–2093 (2022)
Kim, J., Astillo, P.V., Sharma, V., Guizani, N., You, I.: MoTH: mobile terminal handover security protocol for HUB switching based on 5G and beyond (5GB) P2MP backhaul environment. IEEE Internet Things J. 9(16), 14667–14684 (2022)
Wang, J., Hong, Z., Zhang, Y., **, Y.: Enabling security-enhanced attestation with Intel SGX for remote terminal and IoT. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 37(1), 88–96 (2018)
Hossain, M., **e, J.: Hidden terminal emulation: an attack in dense IoT networks in the shared spectrum operation. In: 2019 IEEE Global Communications Conference (GLOBECOM), pp. 1–6 (2019)
Hossain, M., **e, J.: Third eye: context-aware detection for hidden terminal emulation attacks in cognitive radio-enabled IoT networks. IEEE Trans. Cogn. Commun. Netw. 6(1), 214–228 (2020)
Sanz, I.J., Lopez, M.A., Menezes Ferrazani Mattos, D., Muniz Bandeira Duarte, O.C.: A cooperation-aware virtual network function for proactive detection of distributed port scanning. In: 2017 1st Cyber Security in Networking Conference (CSNet), pp. 1–8 (2017)
Aparicio-Navarro, F.J., Kyriakopoulos, K.G., Gong, Y., Parish, D.J., Chambers, J.A.: Using pattern-of-life as contextual information for anomaly-based intrusion detection systems. IEEE Access 5, 22177–22193 (2017)
Akiyoshi, R., Kotani, D., Okabe, Y.: Detecting emerging large-scale vulnerability scanning activities by correlating low-interaction honeypots with darknet. In: 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC), pp. 658–663 (2018)
Gallardo, J.L., Ahmed, M.A., Jara, N.: LoRa IoT-based architecture for advanced metering infrastructure in residential smart grid. IEEE Access 9, 124295–124312 (2021)
Wu, J., et al.: Energy efficient 5G LoRa ad-hoc network for smart grid communication. In: 2021 IEEE 11th International Conference on Electronics Information and Emergency Communication (ICEIEC), pp. 1–4 (2021)
Acknowledgments
This work is supported by Science and Technology Project of State Grid Corporation of China (No. 5700-202124182A-0-0-00).
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Chen, T., Cao, C., Ni, P. (2023). An Intelligent IoT Terminal Detection System Based on Data Sniffing. In: Tian, Y., Ma, T., Jiang, Q., Liu, Q., Khan, M.K. (eds) Big Data and Security. ICBDS 2022. Communications in Computer and Information Science, vol 1796. Springer, Singapore. https://doi.org/10.1007/978-981-99-3300-6_49
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DOI: https://doi.org/10.1007/978-981-99-3300-6_49
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