Intelligent Vision-Based Malware Detection and Classification Using Deep Random Forest Paradigm

Intelligent Vision-Based Malware Detection and Classification Using Deep Random Forest Paradigm

Malware is a rapidly increasing menace to modern computing. Malware authors continually incorporate various sophisticated features like code obfuscations to create malware variants and elude detection by existing malware detection systems. The classification of unseen malware variants with similar c...

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Bibliographic Details
Main Authors: S. Abijah Roseline, S. Geetha, Seifedine Kadry, Yunyoung Nam
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Malware
malware classification
malware detection
malware images
malware variants
malware visualization
Online Access:https://ieeexplore.ieee.org/document/9250472/

Internet

https://ieeexplore.ieee.org/document/9250472/

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