免疫-BP神经网络的入侵检测技术系统设计

An Intrusion Detection Algorithm Based on Immune-BP Neural Network

为了能够及时检测出计算机网络系统中的入侵行为,提高网络系统的安全性,文章在BP对神经网络算法以及生物免疫算法分析后,提出了一种基于免疫-BP神经网络算法的入侵检测技术。利用免疫算法,对网络数据集进行特征提取、预处理后,再通过神经网络算法检测识别入侵者。这种检测技术可有效提高入侵检测的有效性、准确性,并且具有良好的鲁棒性。

In order to timely detect intruders of computer network systems, enhance network security, the immune-BP neural network algorithm-based intrusion detection technology is proposed after the analysis of the BP neural network algorithm and biological immune algorithm. Network data set were extracted and pretreated using immune algorithm, and then the intruder was identified via the neural network algorithm detection. This detection technique can effectively improve the validity and accuracy of the intrusion detection and has a good robustness.