A New Framework for Fraud Detection in Bitcoin Transaction through ensemble stacking model in smart cities

A New Framework for Fraud Detection in Bitcoin Transaction through ensemble stacking model in smart cities

Registration ID: IJNRD_219409

Published ID: IJNRD2405082

DOI: Click Here to Get

Rahul Jaiswal , Shobhit Kumar , Aman Sachan , M.S. Bennet Praba

illicit transaction, Anomaly detection, Signature-based approach, Support Vector machine, Machine Learning.

Bitcoin has garnered a notorious reputation for its association with unlawful activities, ranging from money laundering to facilitating dark web transactions and serving as a preferred method of payment for ransomware in the context of smart cities. While blockchain technology provides inherent security features that prevent unauthorized modifications to transaction records, it falls short in actively detecting and thwarting illicit transactions. Traditional detection techniques, such as heuristic and signature-based approaches, formed the foundation of early detection methods. However, these methods proved inadequate in tackling the intricate complexity of anomaly detection within the Bitcoin network. Recognizing the limitations of conventional approaches, the adoption of machine learning (ML) has emerged as a promising avenue for enhancing anomaly detection capabilities. ML algorithms can be trained on vast datasets containing known malware samples, enabling them to discern subtle patterns and features indicative of illicit transactions. By leveraging ML's ability to analyze large volumes of transaction data, smart cities can bolster their defenses against fraudulent activities in the Bitcoin ecosystem, thereby fostering a safer and more secure digital landscape.

Published Paper   E-Certificate

"A New Framework for Fraud Detection in Bitcoin Transaction through ensemble stacking model in smart cities", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 5, page no.a769-a775, May-2024, Available :https://ijnrd.org/papers/IJNRD2405082.pdf

Volume 9 Issue 5, May-2024

Pages : a769-a775

Paper Reg. ID: IJNRD_219409

Published Paper Id: IJNRD2405082

Downloads: 000121137

Research Area: Engineering

Country: Chennai, Tamil Nadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2405082.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2405082

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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