2023
DOI: 10.1016/j.aej.2023.11.015
|View full text |Cite
|
Sign up to set email alerts
|

Unleashing the power of Bat optimized CNN-BiLSTM model for advanced network anomaly detection: Enhancing security and performance in IoT environments

Franciskus Antonius,
J.C. Sekhar,
Vuda Sreenivasa Rao
et al.
Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2024
2024
2025
2025

Publication Types

Select...
4
1
1

Relationship

0
6

Authors

Journals

citations
Cited by 7 publications
(1 citation statement)
references
References 20 publications
0
1
0
Order By: Relevance
“…Convolutional neural networks (CNNs) can be used to extract data features. Many researchers are combining BiLSTM with CNNs for various fields [34][35][36], such as recognition [37,38] and prediction [39]. The selection of hyperparameters is crucial for the performance of the model.…”
Section: Introductionmentioning
confidence: 99%
“…Convolutional neural networks (CNNs) can be used to extract data features. Many researchers are combining BiLSTM with CNNs for various fields [34][35][36], such as recognition [37,38] and prediction [39]. The selection of hyperparameters is crucial for the performance of the model.…”
Section: Introductionmentioning
confidence: 99%