Neuromorphic-IoT-Security

A bio-inspired neuromorphic edge system for real-time cybersecurity in IoT, leveraging Spiking Decision Trees (SDTs) for low-latency, energy-efficient intrusion detection.

Name		Name	Last commit message	Last commit date
Description_stats_Network_dataset		Description_stats_Network_dataset
Figures		Figures
Model		Model
test_network_datasets_postprocessed.py		test_network_datasets_postprocessed.py
.gitattributes		.gitattributes
.gitignore		.gitignore
AggregateEpochInfo.py		AggregateEpochInfo.py
AugmentBalanceIoT23.py		AugmentBalanceIoT23.py
CalculateSummaryStatistics.py		CalculateSummaryStatistics.py
ClusterSpikePatterns.py		ClusterSpikePatterns.py
CompareSpikeRates.py		CompareSpikeRates.py
ExtractFeaturesIoT23.py		ExtractFeaturesIoT23.py
LICENSE		LICENSE
Learning Curve for SNN+RF.png		Learning Curve for SNN+RF.png
LoadInspectIoT23.py		LoadInspectIoT23.py
ProcessedFeatures.zip		ProcessedFeatures.zip
README.md		README.md
SortEventFiles.py		SortEventFiles.py
SpikeEncodingIoT23.py		SpikeEncodingIoT23.py
ValidateBalancedSpikeTrains.py		ValidateBalancedSpikeTrains.py
analyze_integrated_data.py		analyze_integrated_data.py
benchmark_and_validate.py		benchmark_and_validate.py
best_rf_model.pkl		best_rf_model.pkl
compare_models_visualizations.py		compare_models_visualizations.py
eeg_spike_encoding.py		eeg_spike_encoding.py
feature_importance_comparison.png		feature_importance_comparison.png
fig_confusion_matrices.png		fig_confusion_matrices.png
from sklearn.cluster import KMeans.py		from sklearn.cluster import KMeans.py
integrate_iot_eeg_data.py		integrate_iot_eeg_data.py
integrated_dataset_2GB.py		integrated_dataset_2GB.py
integrated_dataset_500MB.py		integrated_dataset_500MB.py
integrated_dataset_50MB.py		integrated_dataset_50MB.py
iot23_code.py		iot23_code.py
iot_results_visualization.py		iot_results_visualization.py
lstm_model.h5		lstm_model.h5
model.py		model.py
model_accuracy_comparison_bar.png		model_accuracy_comparison_bar.png
model_precision_iot_datasets.png		model_precision_iot_datasets.png
preprocess_integrated_dataset.py		preprocess_integrated_dataset.py
preprocess_network_data.py		preprocess_network_data.py
random_forest_model.pkl		random_forest_model.pkl
rf_confusion_matrix.png		rf_confusion_matrix.png
rf_model_no_pca.pkl		rf_model_no_pca.pkl
rf_model_with_pca.pkl		rf_model_with_pca.pkl
sdt_learning_curve_with_gap.png		sdt_learning_curve_with_gap.png
snn+rf_confusion_matrix.png		snn+rf_confusion_matrix.png
snn_model.pth		snn_model.pth
snn_rf_learning_curve.png		snn_rf_learning_curve.png
spiking_decision_tree.pkl		spiking_decision_tree.pkl
test_network_crossvalidation.py		test_network_crossvalidation.py
test_network_datasets.py		test_network_datasets.py
test_saved_models_on_iot_datasets.py		test_saved_models_on_iot_datasets.py
train_and_evaluate_models.py		train_and_evaluate_models.py
train_and_evaluate_models_preprocessed.py		train_and_evaluate_models_preprocessed.py
train_and_visualize_sdt.py		train_and_visualize_sdt.py
train_lstm_model.py		train_lstm_model.py
train_random_forest.py		train_random_forest.py
train_random_forest_smote.py		train_random_forest_smote.py
train_snn_model.py		train_snn_model.py
train_snnrf_model.py		train_snnrf_model.py
train_test_model.py		train_test_model.py
verify_preprocessed_data.py		verify_preprocessed_data.py

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