Data Mining for Network Intrusion Detection: A Comparison of Alternative Methods

Dan Zhu; G. Premkumar; Xiaoning Zhang

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Data Mining for Network Intrusion Detection: A Comparison of Alternative Methods

机译：用于网络入侵检测的数据挖掘：替代方法的比较

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Intrusion detection systems help network administrators prepare for and deal with net- work security attacks. These systems collect information from a variety of systems and network sources, and analyze them for signs of intrusion and misuse. A variety of tech- niques have been employed for analysis ranging from traditional statistical methods to new data mining approaches. In this study the performance of three data mining meth- ods in detecting network intrusion is examined. An experimental design (3×2×2) is created to evaluate the impact of three data mining methods, two data representation for- mats, and tow data proportion schemes on the classification accuracy of intrusion detec- tion systems.

机译：入侵检测系统可帮助网络管理员准备并应对网络安全攻击。这些系统从各种系统和网络源收集信息，并分析它们是否存在入侵和滥用的迹象。从传统的统计方法到新的数据挖掘方法，已经采用了多种技术进行分析。在这项研究中，检查了三种数据挖掘方法在检测网络入侵方面的性能。创建了一个实验设计（3×2×2），以评估三种数据挖掘方法，两种数据表示形式以及两种数据比例方案对入侵检测系统分类准确性的影响。

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《Decision Sciences》 |2001年第4期|p.635-660|共26页
作者
Dan Zhu; G. Premkumar; Xiaoning Zhang;
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原文格式 PDF
正文语种 eng
中图分类决策学;
关键词
Data Mining; Inductive Learning; Intrusion Detection; Network Security;

机译：数据挖掘;归纳学习;入侵检测;网络安全;

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1. Classifying the Network Intrusion Attacks Using Data Mining Classification Methods and their Performance Comparison [J] . P Srinivasulu, D Nagaraju, P Ramesh Kumar, International journal of computer science and network security . 2009,第6期

机译：使用数据挖掘分类方法对网络入侵攻击进行分类及其性能比较
2. Classifying the Network Intrusion Attacks using Data Mining Classification Methods and their Performance Comparison [J] . P Srinivasulu, D Nagaraju, P Ramesh Kumar, International journal of computer science and network security . 2009,第6期

机译：使用数据挖掘分类方法对网络入侵攻击进行分类及其性能比较
3. Improved intrusion detection method for communication networks using association rule mining and artificial neural networks [J] . Safara Fatemeh, Souri Alireza, Serrizadeh Masoud Communications, IET . 2020,第7期

机译：利用关联规则挖掘和人工神经网络改进了通信网络的入侵检测方法
4. Classifying Network Intrusions:A Comparison of Data Mining Methods [C] . Louis W. Glorfeld, Hillol Bala, Robert Miller Americas conference on information systems;AMCIS 2005 . 2005

机译：网络入侵分类：数据挖掘方法的比较
5. Intrusion detection in wireless networks: A data mining approach. [D] . Nath, Shyam Varan. 2005

机译：无线网络中的入侵检测：一种数据挖掘方法。
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机译：痴呆症预测中的数据挖掘方法：线性判别分析逻辑回归神经网络支持向量机分类树和随机森林的准确性敏感性和特异性的真实数据比较
7. Comparison of Data Mining Techniques for Building Network Intrusion Detection Models [O] . Harsha Kosta, Darshan Bhavesh 2016

机译：建立网络入侵检测模型数据挖掘技术的比较

Data Mining for Network Intrusion Detection: A Comparison of Alternative Methods

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