Ransomware Detection Using Random Forest Technique

Ransomware Detection Using Random Forest Technique

Registration ID: IJNRD_186666

Published ID: IJNRD2301354

DOI: Click Here to Get

Miss.Pradnya Haribhau Kapse , Mr.Abhijit Pawar , Miss.Pooja Lalaso Dhaigude , Miss.Rupali Hanumant Deokate , Miss.Rutuja Manoj Jagtap

Ransomware detection; Machine learning; Random forest; Cyber security

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

Published Paper   E-Certificate

"Ransomware Detection Using Random Forest Technique", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 1, page no.d477-d486, January-2023, Available :https://ijnrd.org/papers/IJNRD2301354.pdf

Volume 8 Issue 1, January-2023

Pages : d477-d486

Paper Reg. ID: IJNRD_186666

Published Paper Id: IJNRD2301354

Downloads: 000121150

Research Area: Engineering

Country: pune, MAHARASHTRA, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2301354.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2301354

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

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

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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