Abstract
As application traffic becomes increasingly complex and voluminous, the need for accurate and fast traffic classification is emphasized, leading to proposals for lightweighting DL-based classifier. Nevertheless, there is still a need for faster and more accurate classification methods for practical deployment. We propose a new traffic classification mechanism using the Filter-and-Refine approach. The proposed method was evaluated public dataset using seven baselines and showed 4%p higher accuracy and about 39 times faster classification speed compared to the state-of-the-art. The source code and dataset are available at https://github.com/pb1069/Network-Traffic-Classification.
Published Version
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