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RAX-ClaMal: Dynamic Android malware classification based on RAX register values
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DOI：10.1016/j.iot.2024.101482.png)
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Detecting malware on Android remains a major challenge because malicious apps use sophisticated evasion techniques. This study presents RAX-ClaMal, a novel approach leveraging dynamic analysis of RAX (Register a Extended) register values for Android malware detection. By extracting and examining the RAX register in the data sections from Dalvik Executable (DEX) files, RAX-ClaMal monitors changes in RAX register values to identify malicious behavior. Employing the Jaccard similarity index for classification, the method achieved a precision of 95.38%, a false positive rate of 1.59%, and an average detection time of 9.54 s per sample on the CICMalDroid2020 dataset. These results underscore the potential of using register values as indicators of malicious activity within Android applications.
Keyword:
Android malware classification
Dynamic analysis
DEX file section
RAX register
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