海量模式高效匹配方法研究

摘要

This paper presents a randomizing fingerprint-based Wu and Manber(WM) algorithm(RFP-WM) ,which can ef-fectively reduce false positives rate by calculating a unique fingerprint for each pattern .Compared with WM algorithm ,RFP-WM al-gorithm greatly reduces the hash collision rate and increases the hit rate ,especially in the massive patterns set .Experiment results show that the performance of the RFP-WM algorithm is more superior than traditional Wu and Manber (WM) algorithm on the larg-er pattern set .%本文提出了一种基于随机指纹模型的Wu and Manber （WM ）算法（Randomizing Fingerprint WM ，RFP-WM ），它通过为每一个模式串计算唯一指纹可以有效降低误报率。与WM算法相比，RFP-WM算法极大地降低了哈希冲突率，提高了命中率，在海量模式集上这一效果更为显著。实验结果表明，相对于传统WM算法，该算法的匹配效率更高，而且模式集的规模越大，性能越优越。