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20 June 2023 Network traffic classification based on multi-head attention and deep metric learning
Zhuo Lv, Bin Lu, Xue Li, Zan Qi
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Proceedings Volume 12715, Eighth International Conference on Electronic Technology and Information Science (ICETIS 2023); 1271521 (2023) https://doi.org/10.1117/12.2682521
Event: Eighth International Conference on Electronic Technology and Information Science (ICETIS 2023), 2023, Dalian, China
Abstract
Network traffic classification plays an important role in network resource management and security. The application of encryption techniques and the rapid increase in the size of network traffic have placed higher demands on traffic classification. In this paper, we design multi-headed attention (MHA) and deep metric learning (DML) in our model for network traffic classification. In addition, MHA-DML also extracts more subtle and highly differentiated features through the improved triplet measurement loss. Experimental results demonstrate that the model achieves the best classification on all three publicly available web traffic datasets. The MHA-DML guarantees detection accuracy even when facing a classification task with many categories.
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Zhuo Lv, Bin Lu, Xue Li, and Zan Qi "Network traffic classification based on multi-head attention and deep metric learning", Proc. SPIE 12715, Eighth International Conference on Electronic Technology and Information Science (ICETIS 2023), 1271521 (20 June 2023); https://doi.org/10.1117/12.2682521
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KEYWORDS
Deep learning
Machine learning
Data modeling
Feature extraction
Matrices
Network security
Internet
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