Intrusion Detection System Using Deep Learning Approaches: A Survey-Reference-Cited by-同舟云学术

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Intrusion Detection System Using Deep Learning Approaches: A Survey

Published:2022-09-23 Issue: Volume: Page:777-790
ISSN:2367-3370
Container-title:International Conference on Innovative Computing and Communications
language:
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Author:

Edmond Kantagba,Nand Parma,Sharma Pankaj

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-2535-1_64

Reference25 articles.

1. Wu Y, Wei D, Feng J (2020) Network attacks detection methods based on deep learning techniques: a survey. Security and communication networks, vol 2020. Hindawi Limited. https://doi.org/10.1155/2020/8872923

2. Wu P, Guo H (2019) LuNet: a deep neural network for network intrusion detection. http://arxiv.org/abs/1909.10031

3. Shone N, Ngoc TN, Phai VD, Shi Q (2018) A deep learning approach to network intrusion detection. IEEE Trans Emerg Topics Comput Intell 2(1):41–50. https://doi.org/10.1109/TETCI.2017.2772792

4. Liao HJ, Richard Lin CH, Lin YC, Tung KY (2013) Intrusion detection system: a comprehensive review. J Netw Comput Appl 36(1):16–24. https://doi.org/10.1016/J.JNCA.2012.09.004

5. LeCun Y, Bengio Y, Hinton G (2015) Deep learning. Nature 521(7553):436–444. https://doi.org/10.1038/nature14539

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