An Enhanced Random Forest-Based Framework for Accurate Intrusion Detection in Modern Network Environments

Key Points

• The research aims to enhance intrusion detection accuracy using a random forest-based framework in modern network environments.
• Developed a novel random forest algorithm for intrusion detection.
• Evaluated the framework's performance in various network scenarios.
• Assessed detection rates against traditional methods.
• Achieved a significant increase in detection accuracy compared to existing methods.
• Reduced false positive rates in network intrusion detection.
• Demonstrated robustness across different network conditions.