Research On Regular Expressions Grouping Based On Shuffled Leaping Algorithm Optimization

With the development of the information society,network resource sharing becomes more and more diverse.In the process of the development of network,network security becomes a serious challenge;therefore,the requirements of network security detection technology are getting higher and higher.Regular expression matching technology is widely used in the field of network content security for its fast,accurate and efficient features,such as deep packet detection.In order to improve the matching efficiency,the regular expression is usually converted into the form of DFA for the pattern matching.However,when the number of rules increases,the number of DFA states rapidly expands,which may lead to high spatial complexity.Effective and efficient grouping of regular expressions is an important method to solve the huge space consumption caused by the state expansion of DFA,and to realize the high performance matching of regular expressions.But some existing grouping schemes fail to achieve the optimal grouping results.Firstly,this paper introduces the research background and significance of regular expression grouping,and briefly summarizes the current research status of regular expression grouping problem at home and abroad.Secondly,this paper describes the basic principle of SFLA,and proposed regular expression grouping algorithm-SFLA-GRE algorithm based on shuffled frog leaping algorithm(improved shuffled frog leaping algorithm for regular expression grouping),which combined with the Becchi algorithm and is used to optimize the regular expression rules.In this algorithm,the position information of the frog is redefined and the individual update formula is improved,and the group update strategy is introduced.For testing the algorithm,the regular expressions test set is extracted randomly in the Linux application layer protocol classifier L7-filter and the open source intrusion detection system Snort random extraction of regular expression test set and then through the regular expression matching engine tools of Becchi open source to generate the corresponding DFA as the experimental data,it use the experimental simulation to illustrate the fact that the SFLA-GRE algorithm can further optimize the grouping of regular expressions,and improve the matching efficiency.Finally,the paper tries to combine shuffled frog leaping algorithm and the ant colony algorithm;then the improved SFLA-ACO-GRE algorithm(grouping regular expressions with SFLA and ACO)is proposed.Besides,an algorithm called QSFLA-GRE(quantum shuffled frog leaping algorithm for grouping regular expression)algorithm is presented,which is integrated into the quantum thought in the SFLA.And it uses the experimental simulation to demonstrate that these two algorithms have some optimization ability in solving the problem of regular expression grouping.