摘要
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,RFPWM),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.
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 .
出处
《电子学报》
EI
CAS
CSCD
北大核心
2014年第6期1220-1224,共5页
Acta Electronica Sinica
基金
国家重点基础研究发展计划“973”计划基金(No.2011CB302605)
国家高技术研究发展计划(“863”计划)基金(No.2011AA010705,No.2012AA012502,No.2012AA012506)
“十一五”国家科技支撑计划(No.2012BAH37B01)