Browsing by Author "Tsao, Ya-Han"

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A Flexible Wildcard-Pattern Matching Accelerator via Simultaneous Discrete Finite Automata
(2017-12-01)
Tsai, Hsiang-Jen
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Chen, Chien-Chih
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Peng, Yin-Chi
;
Tsao, Ya-Han
;
Chiang, Yen-Ning
Regular expression matching becomes indispensable elements of Internet of Things network security. However, traditional ternary content addressable memory (TCAM) search engine is unable to handle patterns with wildcards, as it precisely tracks only one active state with single transition. This paper proposes a promising simultaneous pattern matching methodology for wildcard patterns by two separated engines to represent discrete finite automata. A key preprocessing to encode possible postfix pattern by a unique key ensures that follow-up patterns can accurately traverse all possible matches with limited hardware resources. This approach is practical and scalable for achieving good performance and low space consumption in network security, and it can be applicable to any regular expressions even with multiwildcard patterns. The experimental results demonstrate that this scheme can efficiently and accurately recognize wildcard patterns by simultaneously tracking only two active states. By adopting SRAM TCAM in the proposed architecture, the energy consumption is reduced to around 39%, compared with the energy consumption using a computing system that contains a large memory lookup and comparison overhead.
Energy- Efficient TCAM Search Engine Design Using Priority- Decision in Memory Technology
(2017-03)
Tsai, Hsiang-Jen
;
Yang, Keng-Hao
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Peng, Yin-Chi
;
Lin, Chien-Chen
;
Tsao, Ya-Han
Ternary content-addressable memory (TCAM)-based search engines generally need a priority encoder (PE) to select the highest priority match entry for resolving the multiple match problem due to the don\'t care (X) features of TCAM. In contemporary network security, TCAM-based search engines are widely used in regular expression matching across multiple packets to protect against attacks, such as by viruses and spam. However, the use of PE results in increased energy consumption for pattern updates and search operations. Instead of using PEs to determine the match, our solution is a three-phase search operation that utilizes the length information of the matched patterns to decide the longest pattern match data. This paper proposes a promising memory technology called priority-decision in memory (PDM), which eliminates the need for PEs and removes restrictions on ordering, implying that patterns can be stored in an arbitrary order without sorting their lengths. Moreover, we present a sequential input-state (SIS) scheme to disable the mass of redundant search operations in state segments on the basis of an analysis distribution of hex signatures in a virus database. Experimental results demonstrate that the PDM-based technology can improve update energy consumption of nonvolatile TCAM (nvTCAM) search engines by 36%-67%, because most of the energy in these search engines is used to reorder. By adopting the SIS-based method to avoid unnecessary search operations in a TCAM array, the search energy reduction is around 64% of nvTCAM search engines.
Energy-Efficient Non-Volatile TCAM Search Engine Design Using Priority-Decision in Memory Technology for DPI
(2015)
Tsai, Hsiang-Jen
;
Yang, Keng-Hao
;
Peng, Yin-Chi
;
Lin, Chien-Chen
;
Tsao, Ya-Han
TCAM-based search engines are widely used in regular expression matching across multiple packets. However, the use of priority encoder results in increased energy consumption of pattern updates and search operations. This work, proposes a promising memory technology, called Priority-Decision in Memory (PDM), which eliminates the need for priority encoders and removes restrictions on ordering, meaning that patterns can be stored in an arbitrary order without sorting their lengths. Moreover, we present a Sequential Input-State Search (SIS) scheme to disable the mass of redundant search operations in state segments, based on the analysis distribution of hex signatures in a virus database. Experimental results demonstrate that PDM-based technology can improve update energy consumption of nvTCAM search engines by 36%similar to 67% because most of the energy in the latter is used to reorder. By adopting the SIS-based method to avoid unnecessarily search operations in a TCAM array, the search energy reduction is around 64% of nvTCAM search engines.