Classification of malware images using reduced feature subsets and multi-class support vector machines (SVM) This work is supported by King Fahd University of Petroleum and Minerals (KFUPM) - Dhahran - Saudi Arabia. Joint work with Dr. Muhammad Imam - Department of Computer Engieering - KFUPM University.
To run the code you need to install the UCSB malware image dataset available at:
https://vision.ece.ucsb.edu/research/signal-processing-malware-analysis
Make sure to have the following folder structure to run the code properly:
Folder name: malimg_paper_dataset_imgs
Sub-folder names:
Adialer.C
Agent.FYI
Allaple.A
Allaple.L
Alueron.gen!J
Autorun.K
C2LOP.gen!g
C2LOP.P
Dialplatform.B
Dontovo.A
Fakerean
Instantaccess
Lolyda.AA1
Lolyda.AA2
Lolyda.AA3
Lolyda.AT
Malex.gen!J
Obfuscator.AD
Rbot!gen
Skintrim.N
Swizzor.gen!E
Swizzor.gen!I
VB.AT
Wintrim.BX
Yuner.A