A fast malware detection algorithm based on objective-oriented association mining

摘要: Objective-oriented association (OOA) mining has been successfully applied in malware detection. One problem of OOA is that the number rules very large, and many are redundant have little capacity to distinguish from benign files. This circumstance seriously affects running speed for In this paper, an API (Application Programming Interface)-based method proposed detecting malware. To increase detection OOA, different strategies presented: improve rule quality, criteria selection remove APIs cannot become frequent items; find strong discrimination power, we define utility evaluate rules; accuracy, a classification based on multiple adopted. The experiments show can significantly OOA. our time cost data reduced by thirty-two percent, fifty percent.