Malware detection using an ensemble of vision models & LLMs

Abstract

Nowdays, cyber attacks using software are increas ing rapidly. Cyber criminals are finding out new ways to make malware and infect networks. Signature based detection is failing. But, image-based analysis & disassembly show signs of new hope. This paper presents an ensemble-based concept which can be used to produce highly-effective security software.

Keywords

Applied Science - Computer Science

Citation

Publication Details

License: Author-retained; open access display by NSRI unless a separate article license states otherwise.

Peer review status: Editorial and integrity screening for archive display; archive placement does not imply formal journal publication by NSRI.

AI disclosure: No AI disclosure is attached to this public record unless stated in the manuscript.

Conflict of interest statement: No conflict of interest statement is attached to this public record unless stated in the manuscript.

References

References are available in the manuscript PDF when provided.