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Computing environments on cellphones, especially smartphones, are becoming more open and general-purpose, thus they also become attractive targets of malware. Cellphone malware not only causes privacy leakage, extra charges, and depletion of battery power, but also generates malicious traffic and drains down mobile network and service capacity. In this work we devise a novel behaviorbased malware detection system named pBMDS, which adopts a probabilistic approach through correlating user inputs
doi:10.1145/1741866.1741874
dblp:conf/wisec/XieZSZ10
fatcat:5etf4ufncfchhpznrfgzgui2lu