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This project focuses on a Hybrid Metaheuristic approach for Feature Selection for IoT based Cybersecurity Intrusion Detection Flow of the project:

  1. Dataset Selection.

  2. Preprocessing.

  3. Statistical Feature Selection.

  4. Metaheuristic Feature Selection.

  5. Deep Learning Classification.

Dataset: IoT ID 20 (Find it here: https://sites.google.com/view/iot-network-intrusion-dataset/home).

Preprocessing: Standard machine learning preprocessing incl. SMOTE, Sampling, Manual Feature Engineering.

Statistical Feature Selection: Pearson Correlation Coefficient.

Metaheuristic Feature Selection: Improved Salp Swarm Algorithm.

Deep Learning Classifiers: DNN,CNN,RNN,GRU,AutoEncoder.

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