Developing a Traffic Analysis Suite for Modified Packet Capture File
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-50482-2_35
Reference17 articles.
1. Papadogiannaki, E., Ioannidis, S.: 2021 A survey on encrypted network traffic analysis applications, techniques, and countermeasures. ACM Comput. Surv. 54(6), Article 123, 1–35 (2021). https://doi.org/10.1145/3457904 (Jan 2022)
2. Tahaei, H., Afifi, F., Asemi, A., Zaki, F., Anuar, N.B.: The rise of traffic classification in IoT networks: A survey. J. Netw. Comput. ppli. 154, 102538 (2020). https://doi.org/10.1016/j.jnca.2020.102538. ISSN 1084–8045
3. Rezaei, S., Liu, X.: Deep learning for encrypted traffic classification: an overview. IEEE Commun. Mag. 57(5), 76–81 (2019). https://doi.org/10.1109/MCOM.2019.1800819
4. Aceto, G., Ciuonzo, D., Montieri, A., Pescapé, A.: Mobile encrypted traffic classification using deep learning: experimental evaluation, lessons learned, and challenges. IEEE Trans. Netw. Serv. Manage. 16(2), 445–458 (2019). https://doi.org/10.1109/TNSM.2019.2899085
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