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Automatic classification of virus samples into a concept hierarchy has been attracting much attention from malware research community. This would help anti-virus experts to have an obvious and systematic view on the landscape of virus samples, whose numbers have been rapidly increasing recently. However, it is not a trivial work, since malwares usually come in binary forms whose actions are complicated and obfuscated. Therefore, the typical data mining approaches based on feature extraction aredoi:10.18178/ijmlc.2017.7.4.619 fatcat:oiwanqmljbbubkyyrm7o2m6hp4