poster

Free access

Towards fast regular expression matching in practice

Authors:

Kai Wang,

Jun LiAuthors Info & Claims

SIGCOMM '13: Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM

Pages 531 - 532

https://doi.org/10.1145/2486001.2491705

Published: 27 August 2013 Publication History

PDF eReader

Abstract

Regular expression matching is popular in today's network devices with deep inspection function, but due to lack of algorithmic scalability, it is still the performance bottleneck in practical network processing. To address this problem, our method first partition regular expression patterns into simple segments to avoid state explosion, and then compile these segments into a compact data structure to achieve fast matching. Preliminary experiments illustrate that our matching engine scales linearly with the size of the real-world pattern set, and outperforms state-of-the-art solutions.

References

[1]

Snort, http://www.snort.org/.

Google Scholar

[2]

DARPA Intrusion Detection Data Sets, http://www.ll.mit.edu/mission/communications/ist/corpora/ideval/data/index.html.

Google Scholar

[3]

M. Becchi and P. Crowley. A hybrid finite automaton for practical deep packet inspection. In Proceedings of the 2007 ACM CoNEXT Conference, pages 1--12. ACM, 2007.

Digital Library

Google Scholar

[4]

R. Smith, C. Estan, S. Jha, and S. Kong. Deflating the big bang: fast and scalable deep packet inspection with extended finite automata. In Proceedings of the 2008 ACM SIGCOMM Conference, pages 207--218. ACM, 2008.

Digital Library

Google Scholar

[5]

F. Yu, Z. Chen, Y. Diao, T. Lakshman, and R. Katz. Fast and memory-efficient regular expression matching for deep packet inspection. In Proceedings of the 2nd ACM/IEEE ANCS Conference, pages 93--102. ACM, 2006.

Digital Library

Google Scholar

Cited By

View all

Yu CYau PCao QSeow CPang PWong D(2024)Machine Learning-Enhanced Automation for Invoice Reconciliation: OCR-Based Solutions for Accuracy and Efficiency in Logistics IndustryIntelligent Systems and Applications10.1007/978-3-031-66336-9_23(325-336)Online publication date: 1-Aug-2024
https://doi.org/10.1007/978-3-031-66336-9_23
Xu CChen SWang XSu J(2015)An Efficient Pre-filter to Accelerate Regular Expression MatchingProceedings of the ICA3PP International Workshops and Symposiums on Algorithms and Architectures for Parallel Processing - Volume 953210.1007/978-3-319-27161-3_10(111-119)Online publication date: 18-Nov-2015
https://dl.acm.org/doi/10.1007/978-3-319-27161-3_10
Wang SZhang MLi GLiu CWang ZLiu YXu M(2023)Bolt: Scalable and Cost-Efficient Multistring Pattern Matching With Programmable SwitchesIEEE/ACM Transactions on Networking10.1109/TNET.2022.320252331:2(846-861)Online publication date: Apr-2023
https://doi.org/10.1109/TNET.2022.3202523
Show More Cited By

Index Terms

Towards fast regular expression matching in practice
1. Security and privacy
  1. Network security

Recommendations

Towards fast regular expression matching in practice

Regular expression matching is popular in today's network devices with deep inspection function, but due to lack of algorithmic scalability, it is still the performance bottleneck in practical network processing. To address this problem, our method first ...
Spectral clustering based regular expression grouping
ANCS '14: Proceedings of the tenth ACM/IEEE symposium on Architectures for networking and communications systems

Regular expression matching has been playing an import role in today's network security systems with deep inspection function. However, compiling a set of regular expressions into one Deterministic Finite Automata (DFA) often leads to state explosion, ...
Chain-Based DFA Deflation for Fast and Scalable Regular Expression Matching Using TCAM
ANCS '11: Proceedings of the 2011 ACM/IEEE Seventh Symposium on Architectures for Networking and Communications Systems

Regular expression matching is the core engine of many network functions such as intrusion detection, protocol analysis and so on. In spite of intensive research, we are still in need of a method for fast and scalable regular expression matching, where ...

Comments

Information & Contributors

Information

Published In

SIGCOMM '13: Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM

August 2013

580 pages

ISBN:9781450320566

DOI:10.1145/2486001

General Chairs:
Dah Ming Chiu
Chinese University of Hong Kong, China
,
Jia Wang
AT&T Labs - Research, USA
,
Program Chairs:
Paul Barford
University of Wisconsin, USA
,
Srinivasan Seshan
Carnegie Mellon University, USA

ACM SIGCOMM Computer Communication Review Volume 43, Issue 4
October 2013
595 pages
ISSN:0146-4833
DOI:10.1145/2534169
Issue’s Table of Contents

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 August 2013

Check for updates

Author Tags

Qualifiers

Poster

Conference

SIGCOMM'13

Sponsor:

SIGCOMM

SIGCOMM'13: ACM SIGCOMM 2013 Conference

August 12 - 16, 2013

Hong Kong, China

Acceptance Rates

SIGCOMM '13 Paper Acceptance Rate 38 of 246 submissions, 15%;

Overall Acceptance Rate 462 of 3,389 submissions, 14%

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

7
Total Citations
View Citations
312
Total Downloads

Downloads (Last 12 months)48
Downloads (Last 6 weeks)7

Reflects downloads up to 10 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Yu CYau PCao QSeow CPang PWong D(2024)Machine Learning-Enhanced Automation for Invoice Reconciliation: OCR-Based Solutions for Accuracy and Efficiency in Logistics IndustryIntelligent Systems and Applications10.1007/978-3-031-66336-9_23(325-336)Online publication date: 1-Aug-2024
https://doi.org/10.1007/978-3-031-66336-9_23
Xu CChen SWang XSu J(2015)An Efficient Pre-filter to Accelerate Regular Expression MatchingProceedings of the ICA3PP International Workshops and Symposiums on Algorithms and Architectures for Parallel Processing - Volume 953210.1007/978-3-319-27161-3_10(111-119)Online publication date: 18-Nov-2015
https://dl.acm.org/doi/10.1007/978-3-319-27161-3_10
Wang SZhang MLi GLiu CWang ZLiu YXu M(2023)Bolt: Scalable and Cost-Efficient Multistring Pattern Matching With Programmable SwitchesIEEE/ACM Transactions on Networking10.1109/TNET.2022.320252331:2(846-861)Online publication date: Apr-2023
https://doi.org/10.1109/TNET.2022.3202523
Han YWang BYang XQiu TZhu H(2019)Efficient regular expression matching on LZ77 compressed strings using negative factorsWorld Wide Web10.1007/s11280-019-00667-z22:6(2519-2543)Online publication date: 23-Mar-2019
https://doi.org/10.1007/s11280-019-00667-z
Xu CChen SSu JYiu SHui L(2016)A Survey on Regular Expression Matching for Deep Packet InspectionIEEE Communications Surveys & Tutorials10.1109/COMST.2016.256666918:4(2991-3029)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1109/COMST.2016.2566669
Wang KLi J(2015)FREME: A pattern partition based engine for fast and scalable regular expression matching in practiceJournal of Network and Computer Applications10.1016/j.jnca.2015.05.01255(154-169)Online publication date: Sep-2015
https://doi.org/10.1016/j.jnca.2015.05.012
Xu CChen SWang XSu J(2015)An Efficient Pre-filter to Accelerate Regular Expression MatchingProceedings of the ICA3PP International Workshops and Symposiums on Algorithms and Architectures for Parallel Processing - Volume 953210.1007/978-3-319-27161-3_10(111-119)Online publication date: 18-Nov-2015
https://dl.acm.org/doi/10.1007/978-3-319-27161-3_10
Wang KFu ZHu XLi J(2014)Practical regular expression matching free of scalability and performance barriersComputer Communications10.1016/j.comcom.2014.08.00554:C(97-119)Online publication date: 1-Dec-2014
https://dl.acm.org/doi/10.1016/j.comcom.2014.08.005

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Towards fast regular expression matching in practice

Spectral clustering based regular expression grouping

Chain-Based DFA Deflation for Fast and Scalable Regular Expression Matching Using TCAM