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)
Nowadays, the ransomware became a serious threat challenge the computing world that requires an immediate consideration to avoid financial and moral blackmail. A new technique that can recognise and thwart this kind of attack is therefore desperately needed. The vast majority of earlier detection techniques used a laborious dynamic analysis strategy. The current work suggests a novel static analysis-based strategy to identify ransomware. The key aspect of the suggested approach is the elimination of the disassembly step in favour of direct feature extraction from the raw byte using frequent pattern mining, which noticeably speeds up detection. The Gain Ratio feature selection method demonstrated that the best number of features for the detection process was 1000.The results showed that tree numbers of 100 with seed number of 1 achieved best results in terms of time-consuming and accuracy. The experimental evaluation revealed that the proposed method could achieve a high accuracy of 97.74% for detection ransomware
Keywords:
Ransomware detection; Machine learning; Random forest; Cyber security
Cite Article:
"Ransomware Detection Using Random Forest Technique", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 1, page no.d477-d486, January-2023, Available :http://www.ijnrd.org/papers/IJNRD2301354.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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