An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA
Network intrusion detection is an essential component of contemporary cybersecurity strategies, and the development of efficient techniques to accurately identify malicious activities has become a priority. This study investigates the performance of various conventional machine learning algorithms,...
Saved in:
Main Authors: | Hui, Bian, Chiew, Kang Leng |
---|---|
Format: | Article |
Language: | English |
Published: |
Semarak Ilmu Publishing
2025
|
Subjects: | |
Online Access: | http://ir.unimas.my/id/eprint/45194/1/ARASETV44_N1_PP225_238%20%28dragged%29.pdf http://ir.unimas.my/id/eprint/45194/ https://semarakilmu.com.my/journals/index.php/applied_sciences_eng_tech/index https://doi.org/10.37934/araset.44.1.225238 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A survey of CNN-based network intrusion detection
by: Mohammadpour, Leila, et al.
Published: (2022) -
CNN-LSTM: hybrid deep neural network for network intrusion detection system; a case
by: Halbouni, Asmaa Hani, et al.
Published: (2022) -
Convolutional neural network long short-term memory (CNN + LSTM) for histopathology cancer image classification
by: Zainudin, Zanariah, et al.
Published: (2020) -
CNN-LSTM: Hybrid deep neural network for network intrusion detection system
by: Halbouni, Asmaa, et al.
Published: (2022) -
An improved LSTM-PCA ensemble classifier for SQL injection and XSS attack detection
by: Stiawan, Deris, et al.
Published: (2023)