IoT Device Identification Based on IP Traffic

Authors

  • Yuanchen Jiang

DOI:

https://doi.org/10.54097/5xa99r80

Keywords:

IoT Security, IoT Device Identification, Random Forest, Network Traffic

Abstract

This study aims to address the challenge of IoT device classification by proposing a method based on the random forest classifier. By analyzing the network traffic characteristics of four common household IoT devices, we constructed a feature set and utilized the RF classifier for device identification. The experimental results demonstrate that the random forest classifier performs excellently in terms of precision, recall, and F1 score. By analyzing the network traffic characteristics of four common household IoT devices, we constructed a feature set that includes 20 important device feature information which can effectively represent device identity characteristics, and used the RF classifier for device identification. We conducted numerous experiments on a publicly available dataset and achieved an accuracy rate of 97.22%. The findings offer valuable references for the development of the IoT device identification field and point out potential directions for future research to further enhance the performance and adaptability of the classifier.

References

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Published

26-12-2024

Issue

Section

Articles

How to Cite

Jiang, Y. (2024). IoT Device Identification Based on IP Traffic. Journal of Computing and Electronic Information Management, 15(3), 138-142. https://doi.org/10.54097/5xa99r80