Efficient Network Traffic Classification and Visualizing Abnormal Part Via Hybrid Deep Learning Approach :  Xception + Bidirectional GRU

Efficient Network Traffic Classification and Visualizing Abnormal Part Via Hybrid Deep Learning Approach : Xception + Bidirectional GRU

HanSeon Joo

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HaYoung Choi

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ChangHui Yun

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MinJong Cheon

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Efficient Network Traffic Classification and Visualizing Abnormal Part Via Hybrid Deep Learning Approach : Xception + Bidirectional GRU

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

HanSeon Joo. 2022. \u201cEfficient Network Traffic Classification and Visualizing Abnormal Part Via Hybrid Deep Learning Approach : Xception + Bidirectional GRU\u201d. Global Journal of Computer Science and Technology - H: Information & Technology GJCST-H Volume 21 (GJCST Volume 21 Issue H3): .

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GJCST Volume 21 Issue H3
Pg. 1- 10

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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GJCST-H Classification: C.2.1

Submission ReceivedJune 6, 2021
Peer Review Double Blind
Handling Editor
Accepted July 1, 2021
Published July 15, 2021

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v1.2

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January 15, 2022

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