Parallel network intrusion detection on reconfigurable platforms

Chun Jason Xue; Zi Ii Shao; Mei Lin Liu; Qing Feng Zhuge; Edwin H.M. Sha

doi:10.1007/978-3-540-77092-3_8

Parallel network intrusion detection on reconfigurable platforms

Chun Jason Xue^*, Zi Ii Shao, Mei Lin Liu, Qing Feng Zhuge, Edwin H.M. Sha

^*Corresponding author for this work

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

Abstract

With the wide adoption of internet into our everyday lives, internet security becomes an important issue. Intrusion detection at the network level is an effective way of stopping malicious attacks at the source and preventing viruses and worms from wide spreading. The key component in a successful network intrusion detection system is a high performance pattern matching engine that can uncover the malicious activities in real time. In this paper, we propose a highly parallel, scalable hardware based network intrusion detection system, that can handle variable pattern length efficiently and effectively. Pattern matchings are completed in O (log M) time where M is the longest pattern length. Implementation is done on a standard off-the-shelf FPGA. Comparison with the other techniques shows promising results.

Original language	English
Title of host publication	Embedded and Ubiquitous Computing - International Conference, EUC 2007, Proceedings
Editors	Tei-Wei Kuo, Tei-Wei Kuo, Tei-Wei Kuo, Edwin Sha, Edwin Sha, Edwin Sha, Minyi Guo, Minyi Guo, Minyi Guo, Laurence T. Yang, Laurence T. Yang, Laurence T. Yang, Zili Shao, Zili Shao, Zili Shao
Publisher	Springer Verlag
Pages	75-86
Number of pages	12
ISBN (Print)	9783540770916
DOIs	https://doi.org/10.1007/978-3-540-77092-3_8
State	Published - 2007
Externally published	Yes
Event	IFIB International Conference on Embedded and Ubiquitous Computing, EUC 2007 - Taipei, Taiwan, Province of China Duration: 17 Dec 2007 → 20 Dec 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4808 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	IFIB International Conference on Embedded and Ubiquitous Computing, EUC 2007
Country/Territory	Taiwan, Province of China
City	Taipei
Period	17/12/07 → 20/12/07

Access to Document

10.1007/978-3-540-77092-3_8

Cite this

Xue, C. J., Shao, Z. I., Liu, M. L., Zhuge, Q. F., & Sha, E. H. M. (2007). Parallel network intrusion detection on reconfigurable platforms. In T.-W. Kuo, T.-W. Kuo, T.-W. Kuo, E. Sha, E. Sha, E. Sha, M. Guo, M. Guo, M. Guo, L. T. Yang, L. T. Yang, L. T. Yang, Z. Shao, Z. Shao, & Z. Shao (Eds.), Embedded and Ubiquitous Computing - International Conference, EUC 2007, Proceedings (pp. 75-86). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4808 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-540-77092-3_8

Xue, Chun Jason ; Shao, Zi Ii ; Liu, Mei Lin et al. / Parallel network intrusion detection on reconfigurable platforms. Embedded and Ubiquitous Computing - International Conference, EUC 2007, Proceedings. editor / Tei-Wei Kuo ; Tei-Wei Kuo ; Tei-Wei Kuo ; Edwin Sha ; Edwin Sha ; Edwin Sha ; Minyi Guo ; Minyi Guo ; Minyi Guo ; Laurence T. Yang ; Laurence T. Yang ; Laurence T. Yang ; Zili Shao ; Zili Shao ; Zili Shao. Springer Verlag, 2007. pp. 75-86 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{3fdf1321e6034e6c9064b09c458b426c,

title = "Parallel network intrusion detection on reconfigurable platforms",

abstract = "With the wide adoption of internet into our everyday lives, internet security becomes an important issue. Intrusion detection at the network level is an effective way of stopping malicious attacks at the source and preventing viruses and worms from wide spreading. The key component in a successful network intrusion detection system is a high performance pattern matching engine that can uncover the malicious activities in real time. In this paper, we propose a highly parallel, scalable hardware based network intrusion detection system, that can handle variable pattern length efficiently and effectively. Pattern matchings are completed in O (log M) time where M is the longest pattern length. Implementation is done on a standard off-the-shelf FPGA. Comparison with the other techniques shows promising results.",

author = "Xue, \{Chun Jason\} and Shao, \{Zi Ii\} and Liu, \{Mei Lin\} and Zhuge, \{Qing Feng\} and Sha, \{Edwin H.M.\}",

year = "2007",

doi = "10.1007/978-3-540-77092-3\_8",

language = "英语",

isbn = "9783540770916",

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

publisher = "Springer Verlag",

pages = "75--86",

editor = "Tei-Wei Kuo and Tei-Wei Kuo and Tei-Wei Kuo and Edwin Sha and Edwin Sha and Edwin Sha and Minyi Guo and Minyi Guo and Minyi Guo and Yang, \{Laurence T.\} and Yang, \{Laurence T.\} and Yang, \{Laurence T.\} and Zili Shao and Zili Shao and Zili Shao",

booktitle = "Embedded and Ubiquitous Computing - International Conference, EUC 2007, Proceedings",

address = "德国",

note = "IFIB International Conference on Embedded and Ubiquitous Computing, EUC 2007 ; Conference date: 17-12-2007 Through 20-12-2007",

}

Xue, CJ, Shao, ZI, Liu, ML, Zhuge, QF & Sha, EHM 2007, Parallel network intrusion detection on reconfigurable platforms. in T-W Kuo, T-W Kuo, T-W Kuo, E Sha, E Sha, E Sha, M Guo, M Guo, M Guo, LT Yang, LT Yang, LT Yang, Z Shao, Z Shao & Z Shao (eds), Embedded and Ubiquitous Computing - International Conference, EUC 2007, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4808 LNCS, Springer Verlag, pp. 75-86, IFIB International Conference on Embedded and Ubiquitous Computing, EUC 2007, Taipei, Taiwan, Province of China, 17/12/07. https://doi.org/10.1007/978-3-540-77092-3_8

Parallel network intrusion detection on reconfigurable platforms. / Xue, Chun Jason; Shao, Zi Ii; Liu, Mei Lin et al.
Embedded and Ubiquitous Computing - International Conference, EUC 2007, Proceedings. ed. / Tei-Wei Kuo; Tei-Wei Kuo; Tei-Wei Kuo; Edwin Sha; Edwin Sha; Edwin Sha; Minyi Guo; Minyi Guo; Minyi Guo; Laurence T. Yang; Laurence T. Yang; Laurence T. Yang; Zili Shao; Zili Shao; Zili Shao. Springer Verlag, 2007. p. 75-86 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4808 LNCS).

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

TY - GEN

T1 - Parallel network intrusion detection on reconfigurable platforms

AU - Xue, Chun Jason

AU - Shao, Zi Ii

AU - Liu, Mei Lin

AU - Zhuge, Qing Feng

AU - Sha, Edwin H.M.

PY - 2007

Y1 - 2007

N2 - With the wide adoption of internet into our everyday lives, internet security becomes an important issue. Intrusion detection at the network level is an effective way of stopping malicious attacks at the source and preventing viruses and worms from wide spreading. The key component in a successful network intrusion detection system is a high performance pattern matching engine that can uncover the malicious activities in real time. In this paper, we propose a highly parallel, scalable hardware based network intrusion detection system, that can handle variable pattern length efficiently and effectively. Pattern matchings are completed in O (log M) time where M is the longest pattern length. Implementation is done on a standard off-the-shelf FPGA. Comparison with the other techniques shows promising results.

AB - With the wide adoption of internet into our everyday lives, internet security becomes an important issue. Intrusion detection at the network level is an effective way of stopping malicious attacks at the source and preventing viruses and worms from wide spreading. The key component in a successful network intrusion detection system is a high performance pattern matching engine that can uncover the malicious activities in real time. In this paper, we propose a highly parallel, scalable hardware based network intrusion detection system, that can handle variable pattern length efficiently and effectively. Pattern matchings are completed in O (log M) time where M is the longest pattern length. Implementation is done on a standard off-the-shelf FPGA. Comparison with the other techniques shows promising results.

UR - https://www.scopus.com/pages/publications/38149123360

U2 - 10.1007/978-3-540-77092-3_8

DO - 10.1007/978-3-540-77092-3_8

M3 - 会议稿件

AN - SCOPUS:38149123360

SN - 9783540770916

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

SP - 75

EP - 86

BT - Embedded and Ubiquitous Computing - International Conference, EUC 2007, Proceedings

A2 - Kuo, Tei-Wei

A2 - Sha, Edwin

A2 - Guo, Minyi

A2 - Yang, Laurence T.

A2 - Shao, Zili

PB - Springer Verlag

T2 - IFIB International Conference on Embedded and Ubiquitous Computing, EUC 2007

Y2 - 17 December 2007 through 20 December 2007

ER -

Xue CJ, Shao ZI, Liu ML, Zhuge QF , Sha EHM. Parallel network intrusion detection on reconfigurable platforms. In Kuo TW, Kuo TW, Kuo TW, Sha E, Sha E, Sha E, Guo M, Guo M, Guo M, Yang LT, Yang LT, Yang LT, Shao Z, Shao Z, Shao Z, editors, Embedded and Ubiquitous Computing - International Conference, EUC 2007, Proceedings. Springer Verlag. 2007. p. 75-86. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-77092-3_8

Parallel network intrusion detection on reconfigurable platforms

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