Research On Efficient Packet Classification Algorithm Based On Rule Matching

At present,information has been widely used in various fields.With the rapid development of network applications and the extreme expansion of the network scale,the demand for security is increasing.The classification of mass message information is an important means to improve the quality of network services,which requires us to seek more efficient algorithm based on rule matching.This paper mainly focuses on the research of message classification algorithm.First,it expounds the existing classification algorithm of message classification algorithm.From the definition,algorithm thought,rule set,classification process,four typical classification algorithms are listed,Grid of tires,Hicuts,RFC and Bloom filter are studied in detail,and the performance evaluation standard is based on the algorithm.Quasi comparison of different algorithms,and explain the advantages and disadvantages of each algorithm.Then,the Hicuts algorithm and the recursive RFC algorithm are used to improve the algorithm.Combining the RFC algorithm with the Hicuts algorithm,an accurate classification method of user message information based on the rule matching is proposed.In the classification and recognition of the network message,the message accurate identifier should be designed,the domain of the filtering rules of each message is obtained,the number of cutting times is determined,and the message space is divided and selected.Select the dimension and quantity of the cutting,calculate the maximum value of the number of rules,select the subspace after the message cutting,make the longest prefix match to the IP address of the Baotou source,select the highest priority rule as the final match result,and complete the rules matching and classification operation of the Internet mass message information.The experimental simulation results show that the proposed method has high accuracy and high transmission rate.It is more efficient in the condition of increasing rule number,shortens the time of classification,reduces the network burden,and lays the foundation for improving the information security of Internet users.