A Survey of Network Traffic Classification Methods Using Machine Learning
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Published:2022-11-29
Issue:7
Volume:48
Page:413-423
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ISSN:0361-7688
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Container-title:Programming and Computer Software
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language:en
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Short-container-title:Program Comput Soft
Author:
Getman A. I.ORCID, Ikonnikova M. K.ORCID
Publisher
Pleiades Publishing Ltd
Reference42 articles.
1. Rezaei, S. and Liu, X., Deep learning for encrypted traffic classification: An overview, IEEE Commun. Mag., 2019, vol. 57, no. 5, pp. 76–81. 2. Jamshidi, S., The applications of machine learning techniques in networking. https://www.cs.uoregon.edu/Reports/AREA-201902-Jamshidi.pdf. Accessed October 30, 2020. 3. Hubballi, N. and Swarnkar, M., BitCoding: Network traffic classification through encoded bit level signatures, IEEE/ACM Trans. Networking, 2018, vol. 26, no. 5, pp. 1–13. 4. Hubballi, N., Swarnkar, M., and Conti, M., BitProb: Probabilistic bit signatures for accurate application identification, IEEE Trans. Network Serv. Manage., 2020, vol. 17, no. 3, pp. 1730–1741. 5. Finamore, A., Mellia, M., Meo, M., and Rossi, D., KISS: Stochastic packet inspection classifier for UDP traffic, IEEE/ACM Trans. Networking, 2010, vol. 18, no. 5, pp. 1505–1515.
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