Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Natural Language-Inspired Multi-label Video Streaming Traffic
  Classification Method Based on Deep Neural Networks   This paper presents a deep-learning based traffic classification method for
identifying multiple streaming video sources at the same time within an
encrypted tunnel. The work defines a novel feature inspired by Natural Language
Processing (NLP) that allows existing NLP techniques to help the traffic
classification. The feature extraction method is described, and a large dataset
containing video streaming and web traffic is created to verify its
effectiveness. Results are obtained by applying several NLP methods to show
that the proposed method performs well on both binary and multilabel traffic
classification problems. We also show the ability to achieve zero-shot learning
with the proposed method.

17
The categories of this paper are: q-fin
26
The categories of this paper are: bayes-an
27
The categories of this paper are: comp-gas
36
The categories of this paper are: cmp-lg
13
The categories of this paper are: quant-ph
10
The categories of this paper are: q-bio
9
The categories of this paper are: nlin
28
The categories of this paper are: alg-geom
21
The categories of this paper are: adap-org
3
The categories of this paper are: physics
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The categories of this paper are: hep-lat
2
The categories of this paper are: math
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
30
The categories of this paper are: q-alg
35
The categories of this paper are: mtrl-th