Enhanced Intrusion Detection in In-Vehicle Networks Using Advanced Feature Fusion and Stacking-Enriched Learning

Computer Science

• Intrusion Detection 100%
• Feature Fusion 100%
• Intrusion Detection System 71%
• Ensemble Learning 42%
• Machine Learning 28%
• Learning System 28%
• Random Decision Forest 28%
• Leaning Parameter 14%
• Feature Extraction 14%
• Decision Tree 14%
• Detection Accuracy 14%
• Denial-of-Service Attack 14%
• Cybersecurity 14%
• Extracted Feature 14%
• Decision Tree Classifier 14%
• Response Time 14%
• Detecting Intrusion 14%
• Resource Requirement 14%
• Network Traffic 14%
• Spoofing 14%
• Authentication Protocol 14%
• Base Classifier 14%
• Spoofing Attack 14%