一种新的应用于数据流关联分析的多模式匹配算法

摘要

基于流数据处理技术的关联分析方法要求有一个快速、高效的模式匹配引擎,模式匹配算法是引擎实现的关键。针对传统多模式匹配算法的缺点,在对AC算法和Wu-Manber算法进行充分研究的基础上,提出了一种能增加了字符匹配跳转距离,减少匹配次数的新的多模式匹配算法——AC-WMN算法,并对该算法进行了性能测试和分析。实验证明该算法能够有效提高模式匹配的处理速度和效率。%The correlation analysis method based on flow data processing technology requires a fast, efficient pattern-matching engine, pattern matching algorithm is the key to the engine to achieve. Match the shortcomings of the algorithm on the basis of the AC algorithm and Wu-Manber algorithm adequately studied, an increase in the characters match the jump distance, to reduce the matching number of new multi-pattern matching algorithm for the traditional muhi-mode-AC-WMN algorithm and the algorithm performance testing and analysis Experiments show that the algorithm can improve the processing speed and efficiency of pattern matching.