A5076483875- Anomaly Detection Techniques and Applications
- Network Security and Intrusion Detection
- Internet Traffic Analysis and Secure E-voting
- Molecular Sensors and Ion Detection
- Advanced Chemical Sensor Technologies
- Advanced Graph Neural Networks
- Complex Network Analysis Techniques
- Gas Sensing Nanomaterials and Sensors
- Bayesian Modeling and Causal Inference
- Neural Networks and Applications
Shaanxi Normal University
2025
Ningbo University
2024
China Astronaut Research and Training Center
2022
China XD Group (China)
2022
As a security defense technique to protect networks from attacks, network intrusion detection model plays crucial role in the of computer systems and networks. Aiming at shortcomings complex feature extraction process insufficient information existing models, an named FCNN-SE, which uses fusion convolutional neural (FCNN) for stacked ensemble (SE) classification, is proposed this paper. The mainly includes two parts, classification. Multi-dimensional features traffic data are first extracted...
In network intrusion detection, using a machine learning method alone has blind spots and low detection accuracy. A stacked ensemble model heterogeneous base-leaners for information security is proposed. Firstly, the convolution neural used to extract deep in original data set, which normalized as input of model. constructing base classifiers, different combinations are enhance diversity classifiers. Experiments on NSL-KDD dataset show that proposed can comprehensively improve accuracy,...