Paper
14 June 2023 IoT device multi-classification using traffic behavior analysis
Jiaqi Shi, Tieming Liu, Yuanyuan Zhang, Huajuan Ren
Author Affiliations +
Proceedings Volume 12708, 3rd International Conference on Internet of Things and Smart City (IoTSC 2023); 127080E (2023) https://doi.org/10.1117/12.2684026
Event: 3rd International Conference on Internet of Things and Smart City (IoTSC 2023), 2023, Chongqing, China
Abstract
The management of Internet of Things (IoT) devices is becoming increasingly complex. One of the reasons is that IoT device manufacturers are different, and there are different degrees of heterogeneity in service, technology, protocol and other aspects. Accurate identification IoT devices connected to the organization network is an effective way to maintain the organization network security. In this paper, we propose a two-stage machine learning method to identify IoT devices by analyzing network traffic. This method uses the futures of the original traffic advance to classify the types of IoT devices. The method is tested on two public datasets, our method classified IoT devices with an accuracy rate of over 99%.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jiaqi Shi, Tieming Liu, Yuanyuan Zhang, and Huajuan Ren "IoT device multi-classification using traffic behavior analysis", Proc. SPIE 12708, 3rd International Conference on Internet of Things and Smart City (IoTSC 2023), 127080E (14 June 2023); https://doi.org/10.1117/12.2684026
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KEYWORDS
Internet of things

Network security

Feature extraction

Machine learning

Information security

Random forests

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