| 基于无监督聚类算法的入侵检测 |
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| 引用本文： | 王飞,钱玉文,王执铨.基于无监督聚类算法的入侵检测[J].南京理工大学学报(自然科学版),2009,33(3). |
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| 作者姓名： | 王飞 钱玉文 王执铨 |
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| 作者单位： | 南京理工大学,自动化学院,江苏,南京,210094 |
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| 摘 要： | 针对应用聚类方法检测入侵中参数人为指定的问题,提出了一种新的基于无监督的聚类算法.该方法不需要人为设置参数并且不受数据输入顺序的影响,聚类的形状是任意的,能够较真实地反映数据分布的具体性状.算法通过比较无类标训练集样本间的距离,根据距离最近的样本首先聚合成类的特性,在每一步聚类结束时,再次比较类间距离以及计算类内数据占总数据的比率来确定异常数据类.实验证明该算法处理未知入侵检测问题的检测率为89.5%,误报率为0.4%.
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| 关 键 词： | 入侵检测 计算机犯罪 探测器 因特网 网络安全 无监督聚类 无类标数据 |
Intrusion Detection Based on Unsupervised Clustering Algorithm |
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| WANG Fei,QIAN Yu-wen,WANG Zhi-quan.Intrusion Detection Based on Unsupervised Clustering Algorithm[J].Journal of Nanjing University of Science and Technology(Nature Science),2009,33(3). |
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| Authors: | WANG Fei QIAN Yu-wen WANG Zhi-quan |
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| Institution: | School of Automation;NUST;Nanjing 210094;China |
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| Abstract: | An unsupervised clustering algorithm is proposed to solve the problem that most of intrusion detections based on clustering algorithm have artificial parameters.This method has no artificial parameter and is not affected by the order of data entrance.The shape of clusters is arbitrary,which can reflect the real distribution of data.By comparing the distances between unlabeled training data,the algorithm merges characters of clusters according to the characters of nearest samples.When each step of clustering... |
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| Keywords: | intrusion detection computer crime detectors internet network security unsupervised clustering unlabeled data |
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