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Optimized Deep Learning for IoT Intrusion Detection by Ahmed Hat is a document available to read on EtoBox.
What is Optimized Deep Learning for IoT Intrusion Detection about?
This paper presents a smart deep learning model for enhanced intrusion detection in IoT systems, addressing limitations in existing methods through comprehensive preprocessing and hyperparameter tuning of XGBoost and Sequential Neural Network algorithms. The proposed models demonstrated high accuracy and low false positive rates across multiple datasets, particularly excelling on the NSL-KDD dataset. The research emphasizes the importance of robust anomaly detection to safeguard sensitive information in the
- Author
- Ahmed Hat
- Language
- EN