[1]陈春玲,商子豪.基于AdaBoost和概率神经网络的入侵检测算法[J].南京师范大学学报(工程技术版),2008,08(04):021-24.
　Chen Chunling,Shang Zihao.Algorithm of Network Intrusion Detection Based on AdaBoost and PNN[J].Journal of Nanjing Normal University(Engineering and Technology),2008,08(04):021-24.
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基于AdaBoost和概率神经网络的入侵检测算法
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南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
08卷
期数:
2008年04期
页码:
021-24
栏目:
出版日期:
2008-12-30

文章信息/Info

Title:
Algorithm of Network Intrusion Detection Based on AdaBoost and PNN
作者:
陈春玲;商子豪;
南京邮电大学计算机学院, 江苏南京210003
Author(s):
Chen Chunling; Shang Zihao
College of Computer Science,Nanjing University of Posts and Telecommunications,Nanjing 210003,China
关键词:
入侵检测;  概率神经网络;  AdaBoost;  ABPNN
Keywords:
intrusion de tection;  probab ilistic neura l netw ork( PNN);  AdaBoost;  ABPNN
分类号:
TP393.08
摘要:
将AdaBoost算法和概率神经网络结合,提出了一种新的概率神经网络模型ABPNN,基于此模型提出一种新的入侵检测算法.该算法对接收到的网络数据进行分析判断,实现入侵方式的自动分类,并且能对新的入侵行为进行分类和记忆.实验证明该算法在入侵检测系统的检测率和误报率方面都有优越的性能表现.
Abstract:
By com bining AdaBoost a lgo rithm w ith probabilistic neural netwo rk ( PNN) , a new probab ilistic neura l ne-t w ork ( ABPNN) m ode l is proposed. Based on th is mode,l a new in trusion detection a lgo rithm is suggested. This algorithm ana ly zes and estim ates the network data rece ived, rea lizes the acctom atic sorting of intrusion m ethods, and at the sam e tim e sorts and m em orizes new types o f intrusion m ethods. Exper iments show that the propo sed algor ithm can g et better perform ance in detection rate and a larm rate.

参考文献/References:

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备注/Memo

备注/Memo:
基金项目: 国家“863”计划( 2006AA01Z219)资助项目.
通讯联系人: 陈春玲, 副教授, 研究方向: 软件技术及其在通信中的应用. E-m ail:clchen@ n jup t. edu. cn
更新日期/Last Update: 2013-04-24