Anomaly detection in grid computing based on vector quantization

Hong Wei Sun; Kwok Yan Lam; Siu Leung Chung; Ming Gu; Jia Guang Sun

doi:10.1007/978-3-540-30208-7_129

Anomaly detection in grid computing based on vector quantization

Hong Wei Sun
, Kwok Yan Lam
, Siu Leung Chung
, Ming Gu
, Jia Guang Sun

Hong Kong Metropolitan University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

3 Citations (Scopus)

Abstract

An efficient and effective intrusion detection model based the Vector Quantization (VQ) technique is proposed. This model is suitable for security monitoring in the grid computing environment. Experimental results based on this model have shown very promising performance in terms of high detection rate and low false alarm rate.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Editors	Hai Jin, Jianhua Sun, Yi Pan, Nong Xiao
Pages	883-886
Number of pages	4
DOIs	https://doi.org/10.1007/978-3-540-30208-7_129
Publication status	Published - 2004

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3251
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Keywords

Grid Computing
Intrusion Detection
Network Security
Vector Quantization

Access to Document

10.1007/978-3-540-30208-7_129

Cite this

Sun, H. W., Lam, K. Y., Chung, S. L., Gu, M., & Sun, J. G. (2004). Anomaly detection in grid computing based on vector quantization. In H. Jin, J. Sun, Y. Pan, & N. Xiao (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 883-886). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3251). https://doi.org/10.1007/978-3-540-30208-7_129

Sun, Hong Wei ; Lam, Kwok Yan ; Chung, Siu Leung et al. / Anomaly detection in grid computing based on vector quantization. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). editor / Hai Jin ; Jianhua Sun ; Yi Pan ; Nong Xiao. 2004. pp. 883-886 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Anomaly detection in grid computing based on vector quantization",

abstract = "An efficient and effective intrusion detection model based the Vector Quantization (VQ) technique is proposed. This model is suitable for security monitoring in the grid computing environment. Experimental results based on this model have shown very promising performance in terms of high detection rate and low false alarm rate.",

keywords = "Grid Computing, Intrusion Detection, Network Security, Vector Quantization",

author = "Sun, \{Hong Wei\} and Lam, \{Kwok Yan\} and Chung, \{Siu Leung\} and Ming Gu and Sun, \{Jia Guang\}",

year = "2004",

doi = "10.1007/978-3-540-30208-7\_129",

language = "English",

isbn = "3540235647",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "883--886",

editor = "Hai Jin and Jianhua Sun and Yi Pan and Nong Xiao",

booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

Sun, HW, Lam, KY, Chung, SL, Gu, M & Sun, JG 2004, Anomaly detection in grid computing based on vector quantization. in H Jin, J Sun, Y Pan & N Xiao (eds), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3251, pp. 883-886. https://doi.org/10.1007/978-3-540-30208-7_129

Anomaly detection in grid computing based on vector quantization. / Sun, Hong Wei; Lam, Kwok Yan; Chung, Siu Leung et al.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). ed. / Hai Jin; Jianhua Sun; Yi Pan; Nong Xiao. 2004. p. 883-886 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3251).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - Anomaly detection in grid computing based on vector quantization

AU - Sun, Hong Wei

AU - Lam, Kwok Yan

AU - Chung, Siu Leung

AU - Gu, Ming

AU - Sun, Jia Guang

PY - 2004

Y1 - 2004

N2 - An efficient and effective intrusion detection model based the Vector Quantization (VQ) technique is proposed. This model is suitable for security monitoring in the grid computing environment. Experimental results based on this model have shown very promising performance in terms of high detection rate and low false alarm rate.

AB - An efficient and effective intrusion detection model based the Vector Quantization (VQ) technique is proposed. This model is suitable for security monitoring in the grid computing environment. Experimental results based on this model have shown very promising performance in terms of high detection rate and low false alarm rate.

KW - Grid Computing

KW - Intrusion Detection

KW - Network Security

KW - Vector Quantization

UR - https://www.scopus.com/pages/publications/35048876372

U2 - 10.1007/978-3-540-30208-7_129

DO - 10.1007/978-3-540-30208-7_129

M3 - Chapter

AN - SCOPUS:35048876372

SN - 3540235647

SN - 9783540235644

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 883

EP - 886

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

A2 - Jin, Hai

A2 - Sun, Jianhua

A2 - Pan, Yi

A2 - Xiao, Nong

ER -

Sun HW, Lam KY, Chung SL, Gu M, Sun JG. Anomaly detection in grid computing based on vector quantization. In Jin H, Sun J, Pan Y, Xiao N, editors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2004. p. 883-886. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-30208-7_129

Anomaly detection in grid computing based on vector quantization

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