Network Device Identification Scheme Based on Network Traffic Analysis
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-7161-9_5
Reference16 articles.
1. Ammar, N., Noirie, L., Tixeuil, S.: Autonomous IoT device identification prototype, 2019 network traffic measurement and analysis conference (TMA), pp. 195–196. https://doi.org/10.23919/TMA.2019.8784517
2. Pashamokhtari, A., Okui, N., Miyake, Y., Nakahara, M., Gharakheili, H.H.: Inferring connected IoT devices from IPFIX records in residential ISP networks. In: 2021 IEEE 46th Conference on Local Computer Networks (LCN), pp. 57–64. https://doi.org/10.1109/LCN52139.2021.9524954
3. Chen, Y., Pan, J., Yu, D., Ma, Y., Yang, Y.: Retransmission-Based TCP Fingerprints for Fine-Grain IoV Edge Device Identification. IEEE Trans. Veh. Technol. 71(7), 7835–7847 (2022). https://doi.org/10.1109/TVT.2022.3169090
4. Tamura, H., Yanagisawa, K., Shirane, A., Okada, K.: Wireless devices identification with light-weight convolutional neural network operating on quadrant IQ transition image. In: 2020 18th IEEE International New Circuits and Systems Conference (NEWCAS), pp. 106–109. https://doi.org/10.1109/NEWCAS49341.2020.9159777
5. Yuan, Y., Peng, L.: Wireless device identification based on improved convolutional neural network model. In: 2018 IEEE 18th International Conference on Communication Technology (ICCT), pp. 683–687. https://doi.org/10.1109/ICCT.2018.8600086
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