Intelligent Cyber Intrusion Detection System
Deep learning CNN-LSTM network on NSL-KDD dataset achieving 95% accuracy.
- Feature Engineering: Developed a deep learning-based IDS using the NSL-KDD dataset, optimizing feature selection with Recursive Feature Elimination (RFE) and a Decision Tree classifier.
- CNN-LSTM Model: Achieved 95% accuracy and 0.94 F1-score with the CNN-LSTM model, demonstrating superior performance in intrusion detection.
- Publication: Research accepted for publication in Elsevier Computers & Security (Q1, IF: 6.8).