Interpretable Malware Classification based on Functional Analysis

Miles Q. Li, Benjamin C. M. Fung

2022

Abstract

Malware is the crux of cyber-attacks, especially in the attacks of critical cyber(-physical) infrastructures, such as financial systems, transportation systems, smart grids, etc. Malware classification has caught extensive attention because it can help security personnel to discern the intent and severity of a piece of malware before appropriate actions will be taken to secure a critical cyber infrastructure. Existing machine learning-based malware classification methods have limitations on either their performance or their abilities to interpret the results. In this paper, we propose 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. Experiment results show that our model outperforms existing state-of-the-art methods in malware family and severity classification and provide meaningful interpretations.

Paper Citation

in Harvard Style

Li M. and Fung B. (2022). Interpretable Malware Classification based on Functional Analysis. In Proceedings of the 17th International Conference on Software Technologies - Volume 1: ICSOFT, ISBN 978-989-758-588-3, pages 500-507. DOI: 10.5220/0011310900003266

in Bibtex Style

@conference{icsoft22,
author={Miles Li and Benjamin Fung},
title={Interpretable Malware Classification based on Functional Analysis},
booktitle={Proceedings of the 17th International Conference on Software Technologies - Volume 1: ICSOFT,},
year={2022},
pages={500-507},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011310900003266},
isbn={978-989-758-588-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Software Technologies - Volume 1: ICSOFT,
TI - Interpretable Malware Classification based on Functional Analysis
SN - 978-989-758-588-3
AU - Li M.
AU - Fung B.
PY - 2022
SP - 500
EP - 507
DO - 10.5220/0011310900003266