A Table Compression Method for Extended Aho-Corasick Automaton

Liu, Yanbing; Yang, Yifu; Liu, Ping; Tan, Jun

doi:10.1007/978-3-642-02979-0_12

Cited by 8 publications

(5 citation statements)

References 13 publications

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“…A technique for improving table (includes state transitions) compression is described by Y. Liu in 2009 [12]. This method reduces huge memory usage of extended Aho corasick.…”

Section: Related Workmentioning

confidence: 99%

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Tile optimization for area in FPGA based hardware acceleration of peptide identification

Vidanagamachchi

Dewasurendra

Ragel

et al. 2011

2011 6th International Conference on Industrial and Information Systems

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Abstract-Advances in life sciences over the last few decades have lead to the generation of a huge amount of biological data. Computing research has become a vital part in driving biological discovery where analysis and categorization of biological data are involved. String matching algorithms can be applied for protein/gene sequence matching and with the phenomenal increase in the size of string databases to be analyzed, software implementations of these algorithms seems to have hit a hard limit and hardware acceleration is increasingly being sought. Several hardware platforms such as Field Programmable Gate Arrays (FPGA), Graphics Processing Units (GPU) and Chip Multi Processors (CMP) are being explored as hardware platforms. In this paper, we take an FPGA hardware exploration and expedite the design time by a design automation technique. Further, our design automation is also optimized for better hardware utilization through optimizing the number of peptides that can be represented in an FPGA tile. The results indicate significant improvements in design time and hardware utilization which are reported in this paper.

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“…A technique for improving table (includes state transitions) compression is described by Y. Liu in 2009 [12]. This method reduces huge memory usage of extended Aho corasick.…”

Section: Related Workmentioning

confidence: 99%

“…Therefore it can be applied to large scale pattern sets. Here they have presented a simple and efficient table compression method to reduce the automation"s space [12].…”

Section: Related Workmentioning

confidence: 99%

Tile optimization for area in FPGA based hardware acceleration of peptide identification

Vidanagamachchi

Dewasurendra

Ragel

et al. 2011

2011 6th International Conference on Industrial and Information Systems

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“…For this purpose the Aho-Corasick algorithm [10] is employed because it is a multi-pattern matching algorithm and it is scalable too [15]. Given a set of bot commands, as the pattern to search for, in the arriving IRC packets, the algorithm constructs a non-deterministic finite automation (NFA), which is employed to match all patterns at once.…”

Section: Detection Using Aho-corasick Nfamentioning

confidence: 99%

Lightweight C&C based botnet detection using Aho-Corasick NFA

Udhayan

Anitha²,

Hamsapriya³

2010

IJNSA

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Botnet distinguishes itself from the previous malware by having the characteristics of a C&C channel, using which a Botmaster can control the constituents of the botnet. Even though protocols like IRC, HTTP and DNS are exploited to incorporate C&C channels, previous analysis have shown that the majority of the botnets are usually based on IRC. Consequently in this paper the Aho-Corasick NFA based detection is proposed to detect the C&C instructions which is exchanged in IRC run botnets. However the ability to detect botnet is limited to the existing bot commands. Therefore a counting process which analyses every IRC messages is introduced to detect the existence of malicious codes. This detection method and various existing methods have been evaluated using real-world network traces. The results show that the proposed C&C Instruction based IRC detection method can detect real-world botnets with high accuracy.

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“…The technique is widely applied in pattern recognition, spelling checking, natural language processing, intrusion detection, spam prevention, search engines, virus removal, worm containment, and bioinformatics. Fast string-matching algorithms have been greatly studied by many researchers in the past three decades [1][2][3][4] . Aho and Corasick [1] proposed a multi-string matching automation but not a complete one.…”

Section: Introductionmentioning

confidence: 99%

Complete automata for fast matching of multiple skewed strings

Wang

et al. 2010

The 2nd International Conference on Information Science and Engineering

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Multiple string matching is required to handle massive amount of data in many applications including pattern recognition, intrusion detection, and biological sequence analysis, etc. However, the matching process is often disturbed by intentional or unintentional skewing of the strings being matched. This paper presents a new automata formation to perform fast and accurate string matching under such disturbances. This automaton will significantly enhance the accuracy of the skewed string matching process. We present a new algorithm for fast skewed string matching based on the new automaton.

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A Table Compression Method for Extended Aho-Corasick Automaton

Cited by 8 publications

References 13 publications

Tile optimization for area in FPGA based hardware acceleration of peptide identification

Tile optimization for area in FPGA based hardware acceleration of peptide identification

Lightweight C&C based botnet detection using Aho-Corasick NFA

Complete automata for fast matching of multiple skewed strings

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