Deep Learning-Based Hybrid Intelligent Intrusion Detection System
Publication type: Journal Article
Publication date: 2021-03-31
scimago Q2
wos Q3
SJR: 0.431
CiteScore: 6.1
Impact factor: 1.7
ISSN: 15462218, 15462226
Computer Science Applications
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Metrics
41
Total citations:
41
Citations from 2024:
20
(48.78%)
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RIS |
BibTex |
MLA
Cite this
GOST
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Khan M. A., Kim Y. Deep Learning-Based Hybrid Intelligent Intrusion Detection System // Computers, Materials and Continua. 2021. Vol. 68. No. 1. pp. 671-687.
GOST all authors (up to 50)
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Khan M. A., Kim Y. Deep Learning-Based Hybrid Intelligent Intrusion Detection System // Computers, Materials and Continua. 2021. Vol. 68. No. 1. pp. 671-687.
Cite this
RIS
Copy
TY - JOUR
DO - 10.32604/cmc.2021.015647
UR - https://doi.org/10.32604/cmc.2021.015647
TI - Deep Learning-Based Hybrid Intelligent Intrusion Detection System
T2 - Computers, Materials and Continua
AU - Khan, Muhammad Azam
AU - Kim, Yangwoo
PY - 2021
DA - 2021/03/31
PB - Tech Science Press
SP - 671-687
IS - 1
VL - 68
SN - 1546-2218
SN - 1546-2226
ER -
Cite this
BibTex (up to 50 authors)
Copy
@article{2021_Khan,
author = {Muhammad Azam Khan and Yangwoo Kim},
title = {Deep Learning-Based Hybrid Intelligent Intrusion Detection System},
journal = {Computers, Materials and Continua},
year = {2021},
volume = {68},
publisher = {Tech Science Press},
month = {mar},
url = {https://doi.org/10.32604/cmc.2021.015647},
number = {1},
pages = {671--687},
doi = {10.32604/cmc.2021.015647}
}
Cite this
MLA
Copy
Khan, Muhammad Azam, and Yangwoo Kim. “Deep Learning-Based Hybrid Intelligent Intrusion Detection System.” Computers, Materials and Continua, vol. 68, no. 1, Mar. 2021, pp. 671-687. https://doi.org/10.32604/cmc.2021.015647.