IPAssess: A Protocol-Based Fingerprinting Model for Device Identification in the IoT
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-47715-7_46
Reference23 articles.
1. Agarwal, S., Oser, P., Lueders, S.: Detecting IoT devices and how they put large heterogeneous networks at security risk. Sensors 19(19), 4107 (2019)
2. Aksoy, A., Gunes, M.H.: Automated iot device identification using network traffic. In: ICC 2019-2019 IEEE International Conference on Communications (ICC), pp. 1–7. IEEE (2019)
3. Alrashdi, I., Alqazzaz, A., Aloufi, E., Alharthi, R., Zohdy, M., Ming, H.: Ad-iot: Anomaly detection of iot cyberattacks in smart city using machine learning. In: 2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC), pp. 0305–0310. IEEE (2019)
4. Ganeriwala, P., Bhattacharyya, S., Muthalagu, R., Nandanwar, S., Gupta, A.: A Protocol-Based Fingerprinting Model for Device Identification in the IoT. IPAssess (2021)
5. Bai, L., Yao, L., Kanhere, S.S., Wang, X., Yang, Z.: Automatic device classification from network traffic streams of internet of things. In: 2018 IEEE 43rd Conference on Local Computer Networks (LCN), pp. 1–9. IEEE (2018)
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