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摘要:
Intrusion detection systems provide additional defense capacity to a networked information system in addition to the security measures provided by the firewalls. This paper proposes an active rule based enhancement to the C4.5 algorithm for network intrusion detection in order to detect misuse behaviors of internal attackers through effective classification and decision making in computer networks. This enhanced C4.5 algorithm derives a set of classification rules from network audit data and then the generated rules are used to detect network intrusions in a real-time environment. Unlike most existing decision tree based approaches, the spawned rules generated and fired in this work are more effective because the information-theoretic approach minimizes the expected number of tests needed to classify an object and guarantees that a simple (but not necessarily the simplest) tree is found. The main advantage of this proposed algorithm is that the generalization ability of enhanced C4.5 decision trees is better than that of C4.5 decision trees. We have employed data from the third international knowledge discovery and data mining tools competition (KDDcup’99) to train and test the feasibility of this proposed model. By applying the enhanced C4.5 algorithm an average detection rate of 93.28 percent and a false positive rate of 0.7 percent have respectively been obtained in this work.
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篇名 An Active Rule Approach for Network Intrusion Detection with Enhanced C4.5 Algorithm
来源期刊 通讯、网络与系统学国际期刊(英文) 学科 工学
关键词 Decision Tree INTRUSION Detection KDD CUP DATASET ENHANCED C4.5
年,卷(期) 2008,(4) 所属期刊栏目
研究方向 页码范围 314-321
页数 8页 分类号 TP39
字数 语种
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研究主题发展历程
节点文献
Decision
Tree
INTRUSION
Detection
KDD
CUP
DATASET
ENHANCED
C4.5
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研究去脉
引文网络交叉学科
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期刊影响力
通讯、网络与系统学国际期刊(英文)
月刊
1913-3715
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
763
总下载数(次)
1
总被引数(次)
0
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