sharlwinkhin / msoft20

Experimental comparison of features and machine learning classifiers for Android malware detection

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msoft20

dataset: sha256 hashes of the Android apps used in MobileSoft20 paper benign_sha256.csv: hashes of the benign samples malware_sha256.csv: hashes of the malware samples

csv_files: features extracted from dataset smsf.csv.gz: static-sequence features scuf.csv.gz: static-use features dmsf.csv.gz: dynamic-sequence features dcuf.csv.gz: dynamic-use features hmsf.csv.gz: hybrid-sequence features hcuf.csv.gz: hybrid-use features Download at https://smu.sg/iwm

scripts: Python scripts for machine learning and deep learning classifiers ml.py: Python script for running machine learning classifiers on the csv_files dl.py: Python script for running deep learning classifiers on the csv_files msoft_env.yml: Python dependencies

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Experimental comparison of features and machine learning classifiers for Android malware detection


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