Malware classification with recurrent networks
作者： Razvan Pascanu , Jack W. Stokes , Hermineh Sanossian , Mady Marinescu , Anil Thomas
DOI: 10.1109/ICASSP.2015.7178304
关键词: Natural language 、 Artificial intelligence 、 Feature vector 、 Classifier (UML) 、 Malware 、 Machine learning 、 False positive rate 、 Recurrent neural network 、 Computer science 、 Pattern recognition 、 Trigram
摘要: Attackers often create systems that automatically rewrite and reorder their malware to avoid detection. Typical machine learning approaches, which learn a classifier based on a …
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