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W ith the im provem ent o f A n d ro id m alware^s resistance o f being detected, trad itio n a l s ta tic analysis has faced some p ro b le m s ,fo r exam ple ,s ignature analysis has a h igh analysis speed,bu t i t suffers repackaging and code confusion problems. Data f lo w analysis is pre ferred fo r its h igh accu racy,bu t i t is critic ized by h igh resources costs. T o deal w ith the above p rob lem s,a new sta tic analysis system was proposed by com bin ing an im proved m u lti-s igna tu re analysis and data f lo w m in ing m ethod to fin d a balance po in t between the accuracy and the e ffic iency, in w h ich no t on ly the m u lti-s ig ­ nature analysis is im proved by using the signatures o f classes and the m ethod , b u t also the frequent data f lo w patterns is m ined in m alware to avoid manual detection. T he resu lt shows the system has be tte r capability in so lv ing the repacka­ g ing o r code confusion prob lem and the w hole detection accuracy approaches 88% .

基于签名与数据流模式挖掘的Android恶意软件检测系统 (Android Static Analysis System Based on Signature and Data Flow Pattern Mining).