The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
A classificação de pacotes tornou-se uma das técnicas de aplicação mais importantes em segurança de rede desde a última década. A técnica envolve um descritor de tráfego ou critérios definidos pelo usuário para categorizar os pacotes em uma classe de encaminhamento específica que estará acessível para tratamento de segurança futuro. Para alcançar uma classificação rápida de pacotes, propomos um novo esquema, Produção Cruzada Hierárquica. Esta abordagem simplifica o procedimento de classificação e diminui as combinações distintas de campos ao decompor hierarquicamente o espaço multidimensional com base no conceito de busca telescópica. Análogo ao uso de telescópios com diferentes potências**, um processo de múltiplas etapas é usado para procurar alvos. No nosso esquema, o espaço multidimensional é dotado de uma propriedade hierárquica que se autodivide em vários subespaços menores, enquanto o procedimento de classificação de pacotes é traduzido em busca recursiva de subespaços correspondentes. O armazenamento necessário do nosso esquema poderia ser significativamente reduzido, uma vez que as especificações de campo distintas dos subespaços são gerenciáveis. O desempenho é avaliado com base em bancos de dados de filtros reais e sintéticos. Os resultados experimentais demonstram a eficácia e escalabilidade do esquema proposto.
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Chun-Liang LEE, Chia-Tai CHAN, Pi-Chung WANG, "Packet Classification with Hierarchical Cross-Producting" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 5, pp. 1117-1126, May 2010, doi: 10.1587/transinf.E93.D.1117.
Abstract: Packet classification has become one of the most important application techniques in network security since the last decade. The technique involves a traffic descriptor or user-defined criteria to categorize packets to a specific forwarding class which will be accessible for future security handling. To achieve fast packet classification, we propose a new scheme, Hierarchical Cross-Producting. This approach simplifies the classification procedure and decreases the distinct combinations of fields by hierarchically decomposing the multi-dimensional space based on the concept of telescopic search. Analogous to the use of telescopes with different powers**, a multiple-step process is used to search for targets. In our scheme, the multi-dimensional space is endowed with a hierarchical property which self-divides into several smaller subspaces, whereas the procedure of packet classification is translated into recursive searching for matching subspaces. The required storage of our scheme could be significantly reduced since the distinct field specifications of subspaces is manageable. The performance are evaluated based on both real and synthetic filter databases. The experimental results demonstrate the effectiveness and scalability of the proposed scheme.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.1117/_p
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@ARTICLE{e93-d_5_1117,
author={Chun-Liang LEE, Chia-Tai CHAN, Pi-Chung WANG, },
journal={IEICE TRANSACTIONS on Information},
title={Packet Classification with Hierarchical Cross-Producting},
year={2010},
volume={E93-D},
number={5},
pages={1117-1126},
abstract={Packet classification has become one of the most important application techniques in network security since the last decade. The technique involves a traffic descriptor or user-defined criteria to categorize packets to a specific forwarding class which will be accessible for future security handling. To achieve fast packet classification, we propose a new scheme, Hierarchical Cross-Producting. This approach simplifies the classification procedure and decreases the distinct combinations of fields by hierarchically decomposing the multi-dimensional space based on the concept of telescopic search. Analogous to the use of telescopes with different powers**, a multiple-step process is used to search for targets. In our scheme, the multi-dimensional space is endowed with a hierarchical property which self-divides into several smaller subspaces, whereas the procedure of packet classification is translated into recursive searching for matching subspaces. The required storage of our scheme could be significantly reduced since the distinct field specifications of subspaces is manageable. The performance are evaluated based on both real and synthetic filter databases. The experimental results demonstrate the effectiveness and scalability of the proposed scheme.},
keywords={},
doi={10.1587/transinf.E93.D.1117},
ISSN={1745-1361},
month={May},}
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TY - JOUR
TI - Packet Classification with Hierarchical Cross-Producting
T2 - IEICE TRANSACTIONS on Information
SP - 1117
EP - 1126
AU - Chun-Liang LEE
AU - Chia-Tai CHAN
AU - Pi-Chung WANG
PY - 2010
DO - 10.1587/transinf.E93.D.1117
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2010
AB - Packet classification has become one of the most important application techniques in network security since the last decade. The technique involves a traffic descriptor or user-defined criteria to categorize packets to a specific forwarding class which will be accessible for future security handling. To achieve fast packet classification, we propose a new scheme, Hierarchical Cross-Producting. This approach simplifies the classification procedure and decreases the distinct combinations of fields by hierarchically decomposing the multi-dimensional space based on the concept of telescopic search. Analogous to the use of telescopes with different powers**, a multiple-step process is used to search for targets. In our scheme, the multi-dimensional space is endowed with a hierarchical property which self-divides into several smaller subspaces, whereas the procedure of packet classification is translated into recursive searching for matching subspaces. The required storage of our scheme could be significantly reduced since the distinct field specifications of subspaces is manageable. The performance are evaluated based on both real and synthetic filter databases. The experimental results demonstrate the effectiveness and scalability of the proposed scheme.
ER -