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The recent growth in network usage has motivated the creation of new malicious code for various purposes, including economic ones. Today’s signature-based anti-viruses are very accurate, but cannot detect new malicious code. Recently, classification algorithms were employed successfully for the detection of unknown malicious code. However, most of the studies use byte sequence n-gram representation of the binary code of the executable files on windows. We propose the use of Dalvik Operation Code on Android, generated by disassembling the application. We then use n-gram of the operation code as features for the classification process. We present a full methodology for the detection of unknown malicious code, based on text categorization concepts. The experiment results show that the method results are in a high accuracy rate. Keywords—malicious; Dalvik operation code; detection

Detecting Unknown Malware on Android by Machine Learning Using the Feature of Dalvik Operation Code