Enhanced Anomaly Detection in Wireless 5G Networks With Hybrid Learning Technique Using AWID3 Dataset

Computer Science

• Anomaly Detection 100%
• Ensemble Learning 100%
• Learning Technique 100%
• Random Decision Forest 100%
• Deep Neural Network 100%
• Logistic Regression 100%
• 5G Mobile Communication 100%
• Intrusion Detection 50%
• Feature Selection 50%
• Intrusion Detection System 50%
• Machine Learning Algorithm 50%
• Network Layer 50%
• Hybrid Approach 50%
• Cyber Attack 50%
• Detection Accuracy 50%
• Superior Performance 50%
• Threat Detection 50%
• Model Benchmark 50%
• Nave Bayes 50%
• IEEE 802.11 50%
• Extreme Gradient Boosting 50%
• Information Gain 50%
• Machine Learning 50%
• Learning System 50%
• Internet-Of-Things 50%
• Wireless Network 50%
• Decision Tree 50%