DocumentCode
2265874
Title
Accelerating DFA Construction by Hierarchical Merging
Author
Liu, Yanbing ; Guo, Li ; Guo, Muyi ; Liu, Ping
fYear
2011
fDate
26-28 May 2011
Firstpage
1
Lastpage
6
Abstract
Regular expression matching is widely used in many network applications to analyze suspicious traffic against predefined signatures, and to discover anomalous events. Deterministic Finite Automaton (DFA), which recognizes a set of regular expressions, is the basic data structure to scan input traffic byte by byte. Though DFA meets the requirement of real-time processing of network traffic, constructing a combined DFA for a set of regular expression signatures is very time-consuming, especially when the signature set is large. To attack this problem, we propose new strategies to accelerate DFA construction. The basic idea of our method is to construct the combined DFA by hierarchical merging of the DFAs of each single regular expression. Our method runs in O(|Q||Σ| In n) time, which is substantially superior to the time complexity O(|Q||Σ|(Σi=1n|Qi|)2) of classical subset construction algorithm. Experiment on real signatures from open-source systems, such as L7-filter, BRO and SNORT, demonstrates that our method performs 45 times faster than the subset construction algorithm on average.
Keywords
computational complexity; data structures; deterministic automata; digital signatures; finite automata; public domain software; security of data; BRO; L7-filter; SNORT; anomalous events discovery; data structure; deterministic finite automaton construction; hierarchical merging; open-source system; predefined signatures; regular expression matching; subset construction algorithm; suspicious traffic analysis; time complexity; Acceleration; Automata; Complexity theory; Data structures; Doped fiber amplifiers; Merging; Open source software;
fLanguage
English
Publisher
ieee
Conference_Titel
Parallel and Distributed Processing with Applications (ISPA), 2011 IEEE 9th International Symposium on
Conference_Location
Busan
Print_ISBN
978-1-4577-0391-1
Electronic_ISBN
978-0-7695-4428-1
Type
conf
DOI
10.1109/ISPA.2011.32
Filename
5951873
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