【摘要】 提出了一种基于后向传播神经网络和特征选择的入侵检测模型。通过使用该模型对经过特征提取后的攻击数据的训练学习,可以有效地识别各种入侵。在经典的KDD1999数据集上的测试说明:该模型与传统的入侵检测模型相比,能够轻便、高效地对攻击模式进行训练学习,从而正确有效地检测网络攻击。更多还原

【Abstract】 This paper proposes a kind of intrusion detection model based on Back Propagation(BP) neural network and feature selection mechanism.It can effectively detect several types of attacks after the process of feature selection and attack feature training.The experiments on classic KDD 1999 dataset demonstrate the model is accurate and effective.更多还原