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基于改进的随机森林算法的入侵检测模型
引用本文:郭山清,高丛,姚建,谢立.基于改进的随机森林算法的入侵检测模型[J].软件学报,2005,16(8):1490-1498.
作者姓名:郭山清  高丛  姚建  谢立
作者单位:1. 南京大学,计算机软件新技术国家重点实验室,江苏,南京,210093;南京大学,计算机科学与技术系,江苏,南京,210093
2. Department of Computer Science,University of Auckland,Auckland,1020,New Zealand
基金项目:Supported by the Natural Foundation of Jiangsu Province of China under Grant No.BK2002073 (江苏省自然科学基金); the National High-Tech Research and Development Plan of China under Grant No.2003AA142010 (国家高技术研究发展计划(863))
摘    要:针对现有入侵检测算法对不同类型的攻击检测的不均衡性和对攻击的响应时间较差的问题.将随机森林算法引入到入侵检测领域,构造了基于改进的随机森林算法的入侵检测模型,并把这种算法用于基于网络连接信息的数据的攻击检测和异常发现.通过对DARPA数据的入侵检测实验,其结果表明,基于改进的随机森林算法的入侵检测模型是可行的、高效的,对数据集DARPA中所包含的4种类型的攻击检测具有良好的均衡性.

关 键 词:入侵检测  随机森林算法  分类树  进化算法
收稿时间:3/7/2004 12:00:00 AM
修稿时间:2004年3月7日

An Intrusion Detection Model Based on Improved Random Forests Algorithm
GUO Shan-Qing,GAO Cong,YAO Jian and XIE Li.An Intrusion Detection Model Based on Improved Random Forests Algorithm[J].Journal of Software,2005,16(8):1490-1498.
Authors:GUO Shan-Qing  GAO Cong  YAO Jian and XIE Li
Abstract:Coupled with the explosion of number of the network-oriented applications, Intrusion Detection as an increasingly popular area is attracting more and more research efforts. Although a number of algorithms have already been presented to tackle this problem, they are unable to achieve balanced detection performance for different types of intrusion and cannot respond as quickly as expected. Employing random forests algorithm (RFA)in intrusion detection, this paper devises an improved variation - IRFA and presents an IRFA based model for intrusion detection in information exchanged through network connections. The feasibility in balanced detection and the effectiveness of this approach are verified by experiments based on DARPA data sets.
Keywords:intrusion detection  random forests algorithm  classified tree  evolutionary algorithm
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