An Improved Convolutional Neural Network Model for Intrusion Detection in Networks
| Title | An Improved Convolutional Neural Network Model for Intrusion Detection in Networks |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Khan, Riaz Ullah, Zhang, Xiaosong, Alazab, Mamoun, Kumar, Rajesh |
| Conference Name | 2019 Cybersecurity and Cyberforensics Conference (CCC) |
| Keywords | Artificial neural networks, CNN, composability, convolution, convolutional neural nets, convolutional neural network algorithm, convolutional neural networks, cyber physical systems, cyber security, feature extraction, improved convolutional neural network model, Intrusion detection, intrusion samples, KDD99 datasets, Kernel, learning (artificial intelligence), low detection rate, machine learning, Metrics, network intrusion detection, network intrusion detection model, Network security, pattern classification, policy-based governance, popular detection technology, pubcrawl, Resiliency, security of data, Support vector machines, traditional machine learning technology |
| Abstract | Network intrusion detection is an important component of network security. Currently, the popular detection technology used the traditional machine learning algorithms to train the intrusion samples, so as to obtain the intrusion detection model. However, these algorithms have the disadvantage of low detection rate. Deep learning is more advanced technology that automatically extracts features from samples. In view of the fact that the accuracy of intrusion detection is not high in traditional machine learning technology, this paper proposes a network intrusion detection model based on convolutional neural network algorithm. The model can automatically extract the effective features of intrusion samples, so that the intrusion samples can be accurately classified. Experimental results on KDD99 datasets show that the proposed model can greatly improve the accuracy of intrusion detection. |
| DOI | 10.1109/CCC.2019.000-6 |
| Citation Key | khan_improved_2019 |
- Kernel
- traditional machine learning technology
- Support vector machines
- security of data
- Resiliency
- pubcrawl
- popular detection technology
- pattern classification
- network security
- network intrusion detection model
- network intrusion detection
- Metrics
- machine learning
- low detection rate
- learning (artificial intelligence)
- Artificial Neural Networks
- KDD99 datasets
- intrusion samples
- Intrusion Detection
- improved convolutional neural network model
- feature extraction
- cyber security
- convolutional neural networks
- convolutional neural network algorithm
- convolutional neural nets
- convolution
- composability
- CNN
- policy-based governance
- cyber physical systems