Learning from Context: Exploiting and Interpreting File Path Information for Better Malware Detection

16 May 2019Adarsh KyadigeEthan M. RuddKonstantin Berlin

Machine learning (ML) used for static portable executable (PE) malware detection typically employs per-file numerical feature vector representations as input with one or more target labels during training. However, there is much orthogonal information that can be gleaned from the \textit{context} in which the file was seen... (read more)

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