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Data Augmentation Based Malware Detection using Convolutional Neural Networks
[article]
2020
arXiv
pre-print
Recently, cyber-attacks have been extensively seen due to the everlasting increase of malware in the cyber world. These attacks cause irreversible damage not only to end-users but also to corporate computer systems. Ransomware attacks such as WannaCry and Petya specifically targets to make critical infrastructures such as airports and rendered operational processes inoperable. Hence, it has attracted increasing attention in terms of volume, versatility, and intricacy. The most important feature
arXiv:2010.01862v1
fatcat:m65kzeod2bfp5au4bj3q67xoua