文章针对网络入侵检测领域的挑战,提出了一种基于深度学习的网络入侵检测方法.文章研究了基于深度学习的网络入侵检测框架,引入了Leaky ReLU激活函数以优化卷积神经网络的性能,并在MATLAB平台上基于KDD Cup 1999 数据集进行了实验验证.实验结果表明,基于Leaky ReLU激活函数的CNN模型在准确率、召回率和F1 值等指标上均优于基于ReLU激活函数的模型.
Research on network intrusion detection technology based on deep learning
This article proposes a deep learning based network intrusion detection method to address the challenges in the field of network intrusion detection.A deep learning based network intrusion detection framework was studied,and the Leaky ReLU activation function was introduced to optimize the performance of convolutional neural networks.Experimental verification was conducted on the KDD Cup 1999 dataset on the MATLAB platform.The experimental results show that the CNN model based on Leaky ReLU activation function outperforms the model based on ReLU activation function in terms of accuracy,recall and F1 value.
deep learningactivation functionnetwork intrusionconvolutional neural network
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