Multi-pattern Matching Algorithm Based on MapReduce and Hadoop

被引：0
|
作者：
Zhang, Wei [1 ]
Li, Baolu [2 ]
Li, Kun [2 ]
机构：
[1] Beijing Informat Sci & Technol Univ, Beijing Key Lab Internet Culture & Digital Dissem, Sch Comp Sci, Beijing, Peoples R China
[2] Beijing Informat Sci & Technol Univ, Sch Comp Sci, Beijing, Peoples R China
来源：
PROCEEDINGS 2013 INTERNATIONAL CONFERENCE ON MECHATRONIC SCIENCES, ELECTRIC ENGINEERING AND COMPUTER (MEC) | 2013年
关键词：
Hadoop; Parallel Scanning; Multi-Pattern Matching;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Large data sets present new challenges when virus scanning; parallel scanning technology could be an effective remedy for this problem. This research is based on MapReduce and Hadoop platforms and aims to improve the efficiency of virus scanning by making the multi-pattern matching Aho-Corsick (AC) algorithm parallel. Experiments show that, for large data sets, parallel scanning is more efficient than traditional stand-alone scanning.
引用
收藏
页码：1856 / 1859
页数：4
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