|本期目录/Table of Contents|

[1]魏德志,王奇光,林丽娜.一种基于数据挖掘的Snort系统的设计与应用[J].集美大学学报(自然科学版),2011,16(5):397-400.
　WEI De-zhiWANG Qi-guang,LIN Li-na.Design and Application of a Snort System Based on Data Mining[J].Journal of Jimei University,2011,16(5):397-400.
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《集美大学学报（自然科学版）》[ISSN:1007-7405/CN:35-1186/N]

卷:
第16卷
期数:
2011年第5期
页码:
397-400
栏目:
数理科学与信息工程
出版日期:
2011-09-25

文章信息/Info

Title:
Design and Application of a Snort System Based on Data Mining
作者:
魏德志; 王奇光; 林丽娜
(集美大学诚毅学院,福建 厦门 361021)
Author(s):
WEI De-zhiWANG Qi-guang; LIN Li-na
(Chengyi College,Jimei UniversityXiamen 361021,China)
关键词:
数据挖掘; 入侵检测; Apriori算法; Snort
Keywords:
data mining; intrusion detection; Apriori algorithm; Snort
分类号:
-
DOI:
-
文献标志码:
-
摘要:
为了提高入侵的检测效率，提出了一种基于数据挖掘的改进的Snort系统.该系统充分利用数据挖掘的入侵检测优点，采用改进的Apriori算法，在Snort原系统基础上增加一个数据异常检测模块，改进了Snort存在的缺点，提高了检测率.通过模拟实验验证和实际网络环境应用分析，得出该系统比原Snort系统具有更高的检测性能，能检测未知的网络入侵，提高计算机系统的安全性
Abstract:
In order to improve the efficiency of intrusion detection,the paper proposed an improved Snort system based on data mining.The system took advantage of the data mining in intrusion detection,and emplayed the improved Apriori algorithm.A data was added anomaly detection module to the Snort system,amended the fault of Snort,and improved the rate of detection.The simulation results and the actual application of the network environment showed that the improved system had a higher performance than the original Snort,and could detect unknown intrusion and enhance the security of computer systems

参考文献/References:

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　JIN Zhi-hong,XU Qi,LAN Hui.The Multi-dimensional Data Analysis and Data Mining for Container Multimodal Transportation[J].Journal of Jimei University,2011,16(5):268.
[2]陈云超,谢加良,林玲,等.基于改进Apriori算法的高校教育满意度关联规则挖掘[J].集美大学学报(自然科学版),2024,29(4):377.
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备注/Memo

备注/Memo:
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更新日期/Last Update: 2018-06-13