Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)

Research on Traffic Recognition Algorithms for Industrial Control Networks based on Deep Learning

Authors
Yixiang Jiang, Wenjuan Wang, Chengting Zhang
Corresponding Author
Yixiang Jiang
Available Online April 2019.
DOI
https://doi.org/10.2991/icmeit-19.2019.96How to use a DOI?
Keywords
Deep learning; Industrial control system; Traffic identification.
Abstract
With the development of industrial control network and the deep integration of industry and information technology, the rapid development of industrial control system has increased dramatically, which has brought huge economic and property losses to industrial control companies. Therefore, a traffic identification technology based on deep learning is proposed, which makes full use of the characteristics of industrial network traffic signs. Combined with experiments, this technology can classify network traffic and effectively identify abnormal traffic in industrial control system network. Compared with traditional classification methods, it not only improves the accuracy of traffic identification, but also reduces the time required for classification.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
Part of series
Advances in Computer Science Research
Publication Date
April 2019
ISBN
978-94-6252-708-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmeit-19.2019.96How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yixiang Jiang
AU  - Wenjuan Wang
AU  - Chengting Zhang
PY  - 2019/04
DA  - 2019/04
TI  - Research on Traffic Recognition Algorithms for Industrial Control Networks based on Deep Learning
PB  - Atlantis Press
SP  - 595
EP  - 601
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-19.2019.96
DO  - https://doi.org/10.2991/icmeit-19.2019.96
ID  - Jiang2019/04
ER  -