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RESEARCH PAPER ON MALWARE IMAGES CLASSIFICATION USING DEEP LEARNING TECHNIQUES BASED CONVOLUTION NEURAL NETWORKS (CNNs)

  • Unique Paper ID: 177727
  • Volume: 11
  • Issue: 12
  • PageNo: 1285-1289
  • Abstract:
  • Malware is designed to damage computers or computer networks. Malware is a general term used to describe any program designed to harm a computer. The thing is to commit a crime, analogous as gaining unauthorized access to a particular system, so as to compromise user security. utmost malware still uses the same law to produce another different form of malware variants. therefore, the capability to classify similar malware variant characteristics into malware families is a good strategy to stop malware The exploration is useful for classifying malware on malware samples presented as byte chart grayscale images. For malware discovery, DL algorithm like modified VGG is used with an image- grounded malware dataset. For experimental setting, the proposed model Mal Net successfully linked malware images. Mal Net was also used to identify malware images and compared it to other trained models. The suggested system produced accurate and precise results.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 12
  • PageNo: 1285-1289

RESEARCH PAPER ON MALWARE IMAGES CLASSIFICATION USING DEEP LEARNING TECHNIQUES BASED CONVOLUTION NEURAL NETWORKS (CNNs)

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Journal no 47859

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