Study on the intrusion detection method of mobile communication network based on convolutional neural network
Traditional intrusion detection methods are mostly based on rule matching or statistical analysis,which can identify known attack patterns.However,the detection effect is not good for unknown new or variant attacks.Therefore,a mobile communication network intrusion detection method based on convolutional neural networks is proposed for research.The experimental results show that the design method has achieved significant results in mobile communication network intrusion detection,with a false alarm rate of only 0.87%and a false alarm rate of only 1.36%,proving that convolutional neural networks have high accuracy and stability in the field of mobile communication network intrusion detection.
万方数据
维普
