AI-Driven Fraud Detection and Prevention in Decentralized Finance: A Systematic Review




Narayan, Madhusudan; Shukla, Pooja; Kanth, Rajeev

Irfan, Mohammad; Elmogy, Mohammed; Gupta, Swati; Khalifa, Fahmi; Dias, Rui Teixeira

PublisherIGI Global

2024

AI-Driven Decentralized Finance and the Future of Finance

91

114

979-8-3693-6321-8

979-8-3693-6323-2

DOIhttps://doi.org/10.4018/979-8-3693-6321-8.ch004

https://doi.org/10.4018/979-8-3693-6321-8.ch004



The chapter explores the transformative potential of artificial intelligence (AI) in the realm of decentralized finance (DeFi), focusing on its application in fraud detection and prevention. Through an in-depth examination of AI-driven methodologies and techniques, particularly machine learning models, natural language processing (NLP), and graph analytics, this study explores how AI is reshaping the landscape of fraud detection within decentralized financial ecosystems. Using a conceptual framework, this study investigates the current state-of-the-art techniques employed in AI-driven fraud detection and prevention in DeFi. It examines the methodologies and applications driving the adoption of AI, elucidating its efficacy in identifying fraudulent activities and enhancing the security of DeFi platforms.



Last updated on 2025-20-02 at 10:35