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基于蚁群优化的正则表达式分组算法 被引量：2

Regular expression grouping algorithm based on ant colony optimization
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摘要 依据Becchi算法的思想基础,提出基于蚁群优化的改进正则表达式分组算法.根据正则表达式间分组的特点,定义正负影响关系的冲突信息和启发函数,构建信息素更新策略.实验结果表明,该算法较Becchi算法能更加客观合理地反映模式集中正则表达式间的优化合并信息,能有效减少状态数量,达到总状态数最优解,降低正则表达式匹配的复杂度. Following the idea of the Becchi algorithm,an improved regular expressions grouping algorithm based on ant colony optimization（GRE-ACO） was introduced.Taking account of the characteristics of regular expressions grouping,GRE-ACO defined the relationship between positive and negative effects of conflict information,a new heuristic function and pheromone update strategy.Comparison with the Becchi algorithm shows that GRE-ACO can reflect the optimizing merge information of the regular expressions more reasonably,reduce the amount of states effectively,and attain the optimal solution of the total number of state.As a result,the GRE-ACO can reduce the complexity of matching algorithm.
作者 蔡良伟 刘思麒 李霞 李军
机构地区 深圳大学信息工程学院 清华大学信息技术研究院
出处 《深圳大学学报（理工版）》 EI CAS 北大核心 2014年第3期279-285,共7页 Journal of Shenzhen University(Science and Engineering)
基金 国家自然科学基金资助项目(61171124)~~
关键词 人工智能 蚁群优化算法 深度包检测 正则表达式 分组算法 冲突信息 信息素 网络安全 artificial intelligence ant colony optimization deep packet detection regular expression（RE） grouping algorithm conflict information pheromone network security
分类号 TP391 [自动化与计算机技术—计算机应用技术] TP393 [自动化与计算机技术—计算机应用技术]
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参考文献19

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二级参考文献54

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共引文献136

同被引文献27

  • 1金晶,苏勇.一种改进的自适应遗传算法[J].计算机工程与应用,2005,41(18):64-69. 被引量：81
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  • 5Yu F, Chen Z F, Diao Y, et al. Fast and memory- efficient regular expression matching for deep packet inspection [ C ]// Proceedings of the 2006 ACM/IEEE symposium on Architecture for networking and communi- cations systems. New York ( USA ) Association for Computing Machinery, 2006: 93-102.
  • 6Becchi M, Cadambi S. Memory-efficient regular expres- sion search using state merging [ C]// The 26th IEEE International Conference on Computer Communications. Anchorage (USA) : IEEE Press, 2007: 1064-1072.
  • 7Becchi M, Crowley P. A hybrid finite automaton for practi- cal deep packet inspection [ C ]//Proceedings of the ACM CoNEXT Conference. New York ( USA ) : Association for Computing Machinery, 2007,1 : 1-12.
  • 8Becchi M, Franklin M, Crowley P. A workload for evalu- ating deep packet inspection architectures [ C ]// IEEE International Symposium on Workload Characterization. Seattle (USA): IEEE Press , 2008: 79-89.
  • 9Yao Tie, Xu Qiang, He Jin. A grouping algorithm based on regular expression similarity for DFA construction [ C ]// IEEE 13th International Conference on Communi- cation Technology ( ICCT ). Jinan ( China ) : IEEE Press, 2011: 671-674.
  • 10He Gang, Wang Yang, Wu Xiaochun. A regular expres- sion grouping algorithm based on partitioning method [ C]//The 3rd IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC). Beijing (China) : IEEE Press, 2012: 271-274.

引证文献2

二级引证文献5

深圳大学学报（理工版）
2014年 第3期

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