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计算机系统应用英文版:2010,19(5):113-115
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基于集成神经网络的智能决策入侵检测系统
(1.后勤工程学院 后勤信息工程系 重庆 400016;2.后勤科学研究所 北京 100071)
Intrusion Detection System Combining Misuse and Anomaly Based on Neural Network Ensemble
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Received:September 09, 2009    Revised:October 27, 2009
中文摘要: 针对传统入侵检测系统存在误报率、漏检率较高的问题,提出了一种将误用入侵检测和异常入侵检测相结合的智能决策入侵检测系统,该系统基于集成神经网络技术,通过D-S证据理论可以将两种技术很好地结合起来,提高入侵检测系统的效率。阐述了该入侵检测系统的总体结构部署以及各组成模块的相应结构设计。
Abstract:Traditional intrusion detection systems always have such problems as distortion and leakage. To solve these problems, this paper puts forward a new intrusion detection system which could combine misuse detection and anomaly detection. The system is based on neural network ensemble and it uses D-S evidence theory to combine the two intrusion detection technologies. The paper also expatiates on the main structure of the intrusion detection system and the composing module designation.
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陈晓,夏威,包文.基于集成神经网络的智能决策入侵检测系统.计算机系统应用,2010,19(5):113-115
CHEN Xiao,XIA Wei,BAO Wen.Intrusion Detection System Combining Misuse and Anomaly Based on Neural Network Ensemble.COMPUTER SYSTEMS APPLICATIONS,2010,19(5):113-115