Image-Based Malware Classification: A Systematic Literature Review

Malware, a shortened term for malicious software, refers to software or code designed to harm targets using malicious activities. Effective classification of malware is essential for developing robust detection and prevention mechanisms. This study presents a systematic review of the literature on image-based malware classification. The research methodology employed the DICARe technique. The results and discussion section revealed that 31 papers met the criteria and were highly quality. The study also examined the distribution of research on image-based malware classification by country of origin, with contributions from 15 different countries. Various classification techniques were identified in the literature, indicating the continuous development and evolution of solutions in this area. The findings suggest increased research output due to the growing importance of cybersecurity and increased funding for research in this field. This study provides valuable insights into the current state of image-based malware classification research and highlights the need for further advancements in this area.