Hybrid optimised deep learning model for detecting malicious nodes in mobile network

Key Points

• The aim is to develop a hybrid deep learning model to identify malicious nodes within mobile networks effectively.
• Developed a hybrid optimized deep learning model to enhance detection accuracy.
• Implemented in a simulated mobile network environment to assess model performance.
• Utilized various detection algorithms to compare effectiveness.
• Achieved a detection accuracy of over 92% with the hybrid model.
• Significantly reduced false positives, improving network security measures.
• Demonstrated superior performance compared to traditional detection methods.