A CNN trained on images made from runtime API call argument patterns classifies Windows PE malware into seven families plus benign with a reported average accuracy of 98.36%.
”Visual Malware Classification Using a CNN.” In 2024 IEEE MIT Undergraduate Research Technology Conference (URTC) , pp
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion
A CNN trained on images made from runtime API call argument patterns classifies Windows PE malware into seven families plus benign with a reported average accuracy of 98.36%.