Research on Traffic Recognition Algorithms for Industrial Control Networks based on Deep Learning
Yixiang Jiang, Wenjuan Wang, Chengting Zhang
Available Online April 2019.
- https://doi.org/10.2991/icmeit-19.2019.96How to use a DOI?
- Deep learning; Industrial control system; Traffic identification.
- 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.
- 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 -