INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Malware remains a significant security concern in today's digital landscape, with traditional detection methods often proving ineffective against evolving threats. Recent approaches leverage machine learning algorithms, particularly deep learning, to analyze malware effectively. However, existing research is often biased due to training data limitations. To address this, this study evaluates classical machine learning and deep learning models for malware detection using diverse datasets. A novel image processing technique is also proposed to enhance detection accuracy. Results show deep learning outperforming traditional methods, paving the way for scalable and real-time malware detection systems.
Keywords:
Python ,Django ,Mysql ,Wampserver,1. Processor: Pentium IV or higher, RAM: 256 MB,Space on Hard Disk: minimum 512MB,malware detection,
Cite Article:
"ROBUST INTELLIGENT MALWARE DETECTION USING DEEP LEARING AND MACHINE LEARNING", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.d41-d46, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404306.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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