Lightweight Hybrid Deep Learning Architecture and Model for Security in IIOT
Abstract
:1. Introduction
2. Background and Related Work
3. Proposed Hybrid Model CNN-LSTM
4. Results and Discussion
4.1. Preprocessing and Testing
4.2. Steps to Load Data
4.3. Analysis and Discussion
Performance Metrics
- Accuracy: It is the percentage of those predictions which are correct to the total True Positive predictions made by the model.
- Recall: It is the ratio of the percentage as true predictions over an actual number of true predictions made by the model.
- Precision: It is defined as the ratio of the true predictions which are actual over the total true predictions made by the model.
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Ref.No | Dataset | ML/DL Classifier | Type of Attack | Accuracy |
---|---|---|---|---|
[4] | KDDCUP99 | CNN | DoS | 92.9% |
[11] | CAIDA | WDLSTM | anomaly detection | 96.7% |
[15] | KDDCUP99 | CNN | Malware | 97.2% |
[16] | NSL-KDD | DBN | DoS | 96.3% |
[17] | DARPA | GBRBM-DNN | Fault Detection | 98.5% |
[18] | CICIDS and NSL-KDD | Bi-LSTM | Failure Detection | 95.5% |
Our Model | UNSW NB 15 | Hybrid Model | Various types of attacks | 99% |
Hyperparameters | Values |
---|---|
size of batches | 250 |
epoch | 60 |
number of classes | 10 |
activation function | relu |
pooling | softmax |
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Ankita; Rani, S.; Singh, A.; Elkamchouchi, D.H.; Noya, I.D. Lightweight Hybrid Deep Learning Architecture and Model for Security in IIOT. Appl. Sci. 2022, 12, 6442. https://doi.org/10.3390/app12136442
Ankita, Rani S, Singh A, Elkamchouchi DH, Noya ID. Lightweight Hybrid Deep Learning Architecture and Model for Security in IIOT. Applied Sciences. 2022; 12(13):6442. https://doi.org/10.3390/app12136442
Chicago/Turabian StyleAnkita, Shalli Rani, Aman Singh, Dalia H. Elkamchouchi, and Irene Delgado Noya. 2022. "Lightweight Hybrid Deep Learning Architecture and Model for Security in IIOT" Applied Sciences 12, no. 13: 6442. https://doi.org/10.3390/app12136442
APA StyleAnkita, Rani, S., Singh, A., Elkamchouchi, D. H., & Noya, I. D. (2022). Lightweight Hybrid Deep Learning Architecture and Model for Security in IIOT. Applied Sciences, 12(13), 6442. https://doi.org/10.3390/app12136442