MAL2IMAGE: Hybrid Image Transformation for Malware Classification

Author (ESR): 
Ly Vu Duc (Universita Degli Studi Di Trento)
Duc-Ly Vu
Nguyen Trong Kha
Fabio Massacci
Tam V. Nguyen
Phu H. Phung


Existing image transformation approaches (e.g. Nataraj et al. [1], Liu 2016 [2]) for malware detection only perform simple transformation methods that have not considered color encoding and pixel rendering techniques on the performance of machine learning classifiers.

Aims of the research: We propose a new approach to encode and arrange bytes from a binary file into images. These developed images contain statistical (e.g., entropy) and syntactic artifacts (e.g., strings) and their pixels are filled up using Hilbert curves.

16th Conference on Detection of Intrusions and Malware & Vulnerability Assessment
Thursday, August 1, 2019