Security in computing
Self-organizing maps
Comparison of SOM point densities based on different criteria
Neural Computation
Visual Reverse Engineering of Binary and Data Files
VizSec '08 Proceedings of the 5th international workshop on Visualization for Computer Security
A survey of data mining techniques for malware detection using file features
Proceedings of the 46th Annual Southeast Regional Conference on XX
Malware images: visualization and automatic classification
Proceedings of the 8th International Symposium on Visualization for Cyber Security
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This paper concentrates on visualizing computer viruses without using virus specific signature information as a prior stage of the very important problem of detecting computer viruses. In this paper, we address the fact that each viruses have its own character to be distinguished although it is inserted in the executable file. They cannot hide their own feature through the SOM visualization; this feature is like a DNA to determine an individual's unique genetic code. We present how virus codes affect the whole program projection. Without each virus signature, we present how the virus pattern in Windows executable files tells us their family. We show that the variant of each virus also can be covered with each virus mask, which is produced by SOM. We also present the file structure based SOMs of Windows executable files.