计算机工程2012，Vol.38Issue(6)：148-150,3.DOI:10.3969/j.issn.1000-3428.2012.06.048
基于BP神经网络的入侵检测算法
Intrusion Detection Algorithm Based on BP Neural Network
摘要
Abstract
Traditional intrusion detection algorithm for the existence of a relatively high false negative rate and high false alarm rate defects, based on the advantages of BP neural network algorithm, this paper proposes a new algorithm that uses genetic algorithm to optimize BP neural network algorithm for the intrusion detection. The genetic algorithm finds the most appropriate BP neural network weights, and uses the optimized BP neural network learning and network intrusion detection data. Algorithm effectively improves the classification accuracy of BP neural network. Matlab simulation experimental results show that the training samples of the proposed detection algorithm have less time, with better recognition rate and detection rate, compared with traditional intrusion detection algorithm.关键词
BP神经网络/算法优化/入侵检测/漏报率/误报率Key words
BP neural network/ algorithm optimization/ intrusion detection/ false negative rate/ false alarm rate分类
信息技术与安全科学引用本文复制引用
胡明霞..基于BP神经网络的入侵检测算法[J].计算机工程,2012,38(6):148-150,3.
