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Volumn 6, Issue , 2007, Pages 3217-3222

An unsupervised intrusion detection method combined clustering with chaos simulated annealing

Author keywords

Chaos; Intrusion detection; Partitioned clustering; Simulated annealing

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; CHAOTIC SYSTEMS; CLUSTER ANALYSIS; NETWORK SECURITY; SIMULATED ANNEALING;

EID: 38049052560     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMLC.2007.4370702     Document Type: Conference Paper
Times cited : (13)

References (15)
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  • 2
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    • Measuring normality in http traffic for anomaly-based intrusion detection [J]
    • Juan M. Estévez-Tapiador. Measuring normality in http traffic for anomaly-based intrusion detection [J]. Computer networks, 2004, 45: 175-193.
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  • 3
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    • Anomaly intrusion detection method based on HMM [J]
    • Y.Qiao,X.W.Xin,Y.Bin and S.Ge. Anomaly intrusion detection method based on HMM [J]. Electronics letters, 2002, 38(13): 663-664.
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    • Qiao, Y.1    Xin, X.W.2    Bin, Y.3    Ge, S.4
  • 4
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    • Use of k-nearest neighbor classifier for intrusion detection [J]
    • Yihua Liao. Use of k-nearest neighbor classifier for intrusion detection [J]. Computers & security, 2002,21(5): 439-448.
    • (2002) Computers & security , vol.21 , Issue.5 , pp. 439-448
    • Liao, Y.1
  • 6
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    • An evolutionary technique based on K-Means algorithm for optimal clustering in RN[J]
    • Sanghamitra Bandyopadhyay, Ujjwal Maulik. An evolutionary technique based on K-Means algorithm for optimal clustering in RN[J]. Information Sciences, 2002, 146:221 -237.
    • (2002) Information Sciences , vol.146 , pp. 221-237
    • Bandyopadhyay, S.1    Maulik, U.2
  • 7
    • 0041328214 scopus 로고    scopus 로고
    • k*-Means: A new generalized k-means clustering algorithm [J]
    • Yiu-Ming Cheung. k*-Means: A new generalized k-means clustering algorithm [J], Pattern Recognition Letters ,2003,24:2883 - 2893.
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    • Cheung, Y.1
  • 9
    • 0242468747 scopus 로고    scopus 로고
    • An anomaly intrusion detection method by clustering normal user behavior [J]
    • Sang Hyun Oh, et al. An anomaly intrusion detection method by clustering normal user behavior [J]. Computer & security, 2003,22(7):596-612.
    • (2003) Computer & security , vol.22 , Issue.7 , pp. 596-612
    • Sang Hyun, O.1
  • 12
    • 24944449841 scopus 로고    scopus 로고
    • Genetic SOM Clustering Algorithm for Intrusion Detection [J]
    • Zhenying ma. A Genetic SOM Clustering Algorithm for Intrusion Detection [J]. Lecture notes in computer science, ISNN2005, 3498:421-427.
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  • 13
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    • A clustering-based method for unsupervised intrusion detections
    • ShengYi Jiang , Xiaoyu Song,A clustering-based method for unsupervised intrusion detections , Pattern Recognition Letters 2006,27:802 - 810
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  • 14
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    • Donald E. Brown. A Practical Application of Simulated Annealing to Clustering [J]. Pattern Recognition,1992,25(4):401-412.
    • Donald E. Brown. A Practical Application of Simulated Annealing to Clustering [J]. Pattern Recognition,1992,25(4):401-412.
  • 15
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.