期刊文献+

数据挖掘技术在异常检测中的应用 被引量:1

Study on Abnormal Detection Based on System Call and Data Mining Technique
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摘要 入侵检测技术已经成为网络安全领域的研究热点。本文介绍了入侵检测中的数据挖掘技术及其应用,并阐述了基于系统调用和数据挖掘算法的异常入侵检测系统的设计与实现。 The technique of intrusion detection has become a focus in the field ofnetwork security. This paper introduced the categories of intrusion detection and the methods of data mining applied in abnormal detection. It also described the design and implementation of the abnormal IDS based on system call and data mining algorithms.
出处 《微型电脑应用》 2007年第5期16-17,49,共3页 Microcomputer Applications
关键词 系统调用 数据挖掘 入侵检测 Network security System call Data mining RIPPER Intrusion detection
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参考文献6

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同被引文献11

  • 1李川川,刘衍珩,田大新.基于序列模式的网络入侵检测系统[J].吉林大学学报(工学版),2007,37(1):121-125. 被引量:7
  • 2HanJW,KamberM,PeiJ.数据挖掘概念与技术[M].3版.范明,译.北京:机械工业出版社,2012.
  • 3Ren J M, JSR Jang. Discovering time-constrained sequen- tial patterns for music genre classification [ J ]. Audio, Speech, and Language Processing, 2012, 20 ( 4 ) : 1134- 1144.
  • 4Agrawal R, Sriaknt R, Mining sequential patterns [ EB! OL]. [2012-09.-17 ]. http: JJrakesh. agrawal-family, com/ papers/icde 95seq. pdf.
  • 5Pei Jian, Han Jianwei, Behzad M A, et al. PrefixSpan:mining sequential patterns efficiently by prefix-projected pattern growth [ EB/OL]. [2012-09-21 ]. http://pdf, a- miner, org/OO0/300/860/prefixspan _ mining_ sequential _ patterns_by_prefix_projected_growth, pdf.
  • 6Pei Jian, Han Jianwu. Mining sequential patterns by pat- tern-lowth: the prefixSpan approach [ J ]. IEEE Transac- tions on knowledge and data engineering, 2004,16 ( 11 ) : 1424-1440.
  • 7Lin Cindy Xide, Ji Ming, Danilevsky M, et al. Efficient mining of correlated sequential patterns based on null hy- pothesis [ EB/OL ]. [ 2012-09-21 ]. http ://dl. acm. org/ citation, cfm? id = 2389656. 2389660.
  • 8王令剑,滕少华.聚类和时间序列分析在入侵检测中的应用[J].计算机应用,2010,30(3):699-701. 被引量:11
  • 9俞东进,郑苏杭,李万清.基于多核并行的海量数据序列模式挖掘[J].计算机应用研究,2012,29(2):478-481. 被引量:4
  • 10郭小芳,李锋,宋晓宁.一种基于PCA的时间序列异常检测方法[J].江西师范大学学报(自然科学版),2012,36(3):280-283. 被引量:11

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