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Volumn , Issue , 2010, Pages 281-286

Adaptive clustering with feature ranking for DDoS attacks detection

Author keywords

Adaptive clustering; DDoS detection; Feature ranking

Indexed keywords

ADAPTIVE CLUSTERING; ADAPTIVE PROCESS; CLUSTER STRUCTURE; DDOS ATTACK; DDOS DETECTION; DISTRIBUTED DENIAL OF SERVICE ATTACK; FEATURE RANKING; FEATURE VECTORS; INCREMENTAL CLUSTERING ALGORITHM; LINEAR CORRELATION COEFFICIENT; MODIFIED GLOBAL; NETWORK TRAFFIC;

EID: 78650311599     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/NSS.2010.70     Document Type: Conference Paper
Times cited : (31)

References (25)
  • 5
    • 37349125374 scopus 로고    scopus 로고
    • DDoS attack detection method using cluster analysis
    • K. Lee, J. Kim, K. Kwon, Y. Han, and S. Kim, "DDoS Attack Detection Method Using Cluster Analysis," Expert Systems with Applications, vol. 34, no. 3, pp. 1659-1665, 2008.
    • (2008) Expert Systems with Applications , vol.34 , Issue.3 , pp. 1659-1665
    • Lee, K.1    Kim, J.2    Kwon, K.3    Han, Y.4    Kim, S.5
  • 9
    • 85084163540 scopus 로고    scopus 로고
    • CenterTrack: An IP overlay network for tracking DoS floods
    • R. Stone, "CenterTrack: An IP Overlay Network for Tracking DoS Floods," Proc. of the USENIX Security Symposium, 2000.
    • (2000) Proc. of the USENIX Security Symposium
    • Stone, R.1
  • 11
    • 0038059205 scopus 로고    scopus 로고
    • IP traceback with deterministic packet marking
    • A. Belenky and N. Ansari, "IP Traceback with Deterministic Packet Marking," IEEE Communications Letters, vol. 7, no. 4, pp. 162-164, 2003.
    • (2003) IEEE Communications Letters , vol.7 , Issue.4 , pp. 162-164
    • Belenky, A.1    Ansari, N.2
  • 13
    • 0036321445 scopus 로고    scopus 로고
    • Use of K-nearest neighbor classifier for intrusion detection
    • Y. Liao and V. Vemuri, "Use of K-Nearest Neighbor Classifier for Intrusion Detection," Computers & Security, vol. 21, no. 5, pp. 439-448, 2002.
    • (2002) Computers & Security , vol.21 , Issue.5 , pp. 439-448
    • Liao, Y.1    Vemuri, V.2
  • 15
    • 16644393989 scopus 로고    scopus 로고
    • Real-time detection of distributed denial-of-service attacks using RBF networks and statistical features
    • D. Gavrilis and E. Dermatas, "Real-time Detection of Distributed Denial-of-service Attacks Using RBF Networks and Statistical Features," Computer Networks, vol. 48, no. 2, pp. 235-245, 2005.
    • (2005) Computer Networks , vol.48 , Issue.2 , pp. 235-245
    • Gavrilis, D.1    Dermatas, E.2
  • 16
  • 17
    • 0033204902 scopus 로고    scopus 로고
    • An empirical comparison of four initialization methods for the K-means algorithm
    • J. Pena, J. Lozano, and P. Larranaga, "An Empirical Comparison of Four Initialization Methods for the K-means Algorithm," Pattern recognition letters, vol. 20, no. 10, pp. 1027-1040, 1999.
    • (1999) Pattern Recognition Letters , vol.20 , Issue.10 , pp. 1027-1040
    • Pena, J.1    Lozano, J.2    Larranaga, P.3
  • 18
    • 0036487280 scopus 로고    scopus 로고
    • The global K-means clustering algorithm
    • A. Likas, N. Vlassis, and J. J. Verbeek, "The Global K-means Clustering Algorithm," Pattern Recognition, vol. 36, no. 2, pp. 451-461, 2003.
    • (2003) Pattern Recognition , vol.36 , Issue.2 , pp. 451-461
    • Likas, A.1    Vlassis, N.2    Verbeek, J.J.3
  • 19
    • 45549104169 scopus 로고    scopus 로고
    • Modified global K-means algorithm for minimum sumof- squares clustering problems
    • A. Bagirov, "Modified Global K-means Algorithm for Minimum Sumof- squares Clustering Problems," Pattern Recognition, vol. 41, no. 10, pp. 3192-3199, 2008.
    • (2008) Pattern Recognition , vol.41 , Issue.10 , pp. 3192-3199
    • Bagirov, A.1
  • 20
    • 38749139222 scopus 로고    scopus 로고
    • Consensus unsupervised feature ranking from multiple views
    • Y. Hong, S. Kwong, Y. Chang, and Q. Ren, "Consensus Unsupervised Feature Ranking from Multiple Views," Pattern Recognition Letters, vol. 29, no. 5, pp. 595-602, 2008.
    • (2008) Pattern Recognition Letters , vol.29 , Issue.5 , pp. 595-602
    • Hong, Y.1    Kwong, S.2    Chang, Y.3    Ren, Q.4
  • 21
    • 1942451938 scopus 로고    scopus 로고
    • Feature selection for high-dimensional data: A fast correlation-based filter solution
    • L. Yu and H. Liu, "Feature Selection for High-dimensional Data: a Fast Correlation-based Filter Solution," Proc. of International Conference on Machine Learning, 2003, pp. 856-863.
    • (2003) Proc. of International Conference on Machine Learning , pp. 856-863
    • Yu, L.1    Liu, H.2
  • 22
    • 33745561205 scopus 로고    scopus 로고
    • An introduction to variable and feature selection
    • I. Guyon and A. Elisseeff, "An Introduction to Variable and Feature Selection," Journal of Machine Learning Research, vol. 3, pp. 1157-1182, 2003.
    • (2003) Journal of Machine Learning Research , vol.3 , pp. 1157-1182
    • Guyon, I.1    Elisseeff, A.2
  • 23
    • 0032044157 scopus 로고    scopus 로고
    • Information theoretic subset selection for neural network models
    • D. Sridhar, E. Bartlett, and R. Seagrave, "Information Theoretic Subset Selection for Neural Network Models," Computers & Chemical Engineering, vol. 22, no. 4-5, pp. 613-626, 1998.
    • (1998) Computers & Chemical Engineering , vol.22 , Issue.4-5 , pp. 613-626
    • Sridhar, D.1    Bartlett, E.2    Seagrave, R.3
  • 25
    • 27644509863 scopus 로고    scopus 로고
    • [On line]. Available
    • MIT Lincoln Laboratory. (2000). DARPA Intrusion Detection Scenario Specific Datasets [On line]. Available: http://www.ll.mit.edu/mission/ communications/ist/corpora/ideval/data/2000/LLS-DDOS-1.0.html.
    • (2000) DARPA Intrusion Detection Scenario Specific Datasets


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.