Livoa LogoLivoa
Conceptual Framework of ML-Based Intrusion Detection System for IoT
IoT Environment


(Sensors, Devices, Gateways)

IoT Data Streams


(Logs, Packets, Telemetry)

Feature Engineering
Feature Importance Analysis
Feature Selection


(Correlation, Mutual Info)

Data Preprocessing
Feature Encoding


(Label/Categorical Encoding)

Data Cleaning


(Missing Values, Noise Reduction)

Feature Normalisation


(StandardScaler / MinMax)

Machine Learning Models
CatBoost


(Ordered Boosting)

XGBoost


(Gradient Boosting)

Random Forest


(Ensemble Bagging)

Logistic Regression


(Baseline Linear Classifier)

Model Evaluation
Multi-Class Classification


(Confusion Matrix, F1-score)

Binary Classification


(Accuracy, Precision, Recall, AUC)

Feature Importance Visualization
Intrusion Detection Output


Performance Metrics (Optimised IDS Results)

Normal vs Attack (DDoS, Injection, MITM, etc.)

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by Shaan

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