计算机工程2011，Vol.37Issue(23)：124-126,3.
基于量子遗传算法优化神经网络的入侵检测
Intrusion Detection Based on Neural Network Optimized by Quantum Genetic Algorithm
摘要
Abstract
To solve the problem of efficiency and veracity of intrusion detection, this paper presents an intrusion detection model based on quantum genetic algorithm and neural network. The model takes advantage of the global search property of the quantum genetic algorithm and the exact local search characteristics of the BP neural network, and combines quantum genetic algorithm and BP neural network. The weight and the thresholds of the BP neural network are optimized by the improved quantum genetic algorithm, so that the BP neural network enhances efficiency and veracity of intrusion detection, thereby improving network security. Matlab emulating experiments of this model show this method is better than other kinds of methods in detection rate and false alarm rate.关键词
入侵检测/量子遗传算法/智能检测/BP神经网络/网络安全Key words
intrusion detection/ quantum genetic algorithm/ intelligent detection/ BP neural network/ network security分类
天文与地球科学引用本文复制引用
张澎,高守平,王鲁达..基于量子遗传算法优化神经网络的入侵检测[J].计算机工程,2011,37(23):124-126,3.基金项目
湖南省科技计划基金资助项目(2010FJ6028) （2010FJ6028）
湖南省教育厅重点科研基金资助项目(08A064) （08A064）
湖南省高校科研基金资助项目(10C1236) （10C1236）
