Interpretable Malware Classification based on Functional Analysis
Published in ICSOFT 2022, 2022
Recommended citation: Miles Q. Li and Benjamin CM Fung. "Interpretable Malware Classification based on Functional Analysis." In ICSOFT, pp. 500-507. 2022. https://www.scitepress.org/Papers/2022/113109/113109.pdf
This paper proposes a novel malware classification model based on functional analysis of malware samples with the interpretability to show the importance of each function to a classification result. The work integrates an Interpretable Feedforward Neural Network (IFFNN) with a dedicated malware classification model.
Recommended citation: Miles Q. Li and Benjamin CM Fung. “Interpretable Malware Classification based on Functional Analysis.” In ICSOFT, pp. 500-507. 2022.