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IJSDR
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

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Paper Title: Malware Detection Using Image Visualization and Deep Learning
Authors Name: Saksham Tyagi
Unique Id: IJSDR2211027
Published In: Volume 7 Issue 11, November-2022
Abstract: Despite the relentless efforts of cybersecurity research to protect against malware threats, malware developers discover new ways to avoid these defense techniques.Usual machine learning approaches that train a classifier based on handcrafted features are not sufficiently potent against the new evasive techniques and require more efforts due to feature-engineering. We propose a visualization-based method, where malware binaries are depicted as images to successfully distinguish between malware files and clean files using a deep learning model. Extensive experiments performed on Malimg dataset shows the accuracy to improve up to 96.97 percent.
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Cite Article: "Malware Detection Using Image Visualization and Deep Learning", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 11, page no.164 - 166, November-2022, Available :http://www.ijsdr.org/papers/IJSDR2211027.pdf
Downloads: 000336257
Publication Details: Published Paper ID: IJSDR2211027
Registration ID:202474
Published In: Volume 7 Issue 11, November-2022
DOI (Digital Object Identifier): http://doi.one/10.1729/Journal.32139
Page No: 164 - 166
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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