Multi-pattern matching algorithm based on MapReduce and Hadoop

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.