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In order to improve the security of mobile application software based on Android system , a mobile malware detection model is proposed. The model manipulates sensitive API call via data mining to obtain detection rules.To reduce the false positive rate when the rule is used to detect the non malware. a weighted FP-growth association rule mining algorithm is proposed. Based on weighting the sensitive API call, we employ a support threshold to eliminate the rules which preserve small weight and occur with high frequency. The experiments show that the model achevied a detection rate of 81.7% for malwares, and reduced the false positive rate to 11.3%.