摘要
基于机器学习的入侵检测方法是大规模、高带宽网络环境下实现对网络攻击智能检测的关键技术之一。该文对目前主流的基于机器学习的各种入侵检测方法进行了简要介绍和评述,并结合网络攻击的发展趋势,阐述了入侵检测机器学习方法的发展方向。
Intrusion detection techniques based on machine learning is one of the key technologies to be applied to intelligent intrusion detection under the circumstance of large scale and bandwidth network.Many kinds of currently popular intrusion detection techniques based on machine learning are generally introduced and reviewed in this paper,meanwhile,the development prospect of its is presented as well according to the tendency of network attack.
出处
《计算机工程与应用》
CSCD
北大核心
2006年第2期7-10,86,共5页
Computer Engineering and Applications
基金
国家自然科学基金资助项目(编号:60372039)
关键词
入侵检测
机器学习
数据挖掘
神经网络
遗传算法
粗糙集
支持向量机
人工免疫
intrusion detection,machine learning,data mining,neural network,Genetic Algorithm,Rough Set,support vector machine,human immune