(Sasi Institute of Technology and Engineering, India.)
J. Jerin Jose is an Associate Professor in the Department of Artificial Intelligence and Machine Learning at Sasi Institute of Technology and Engineering, India. His research interests include Artificial Intelligence, Machine Learning, Blockchain, and data analytics.
Reena Bansal, J. Jerin Jose. In: AI-Driven Fraud Detection and Financial Crime Prevention in Cloud-Enabled IoT and E-Commerce Ecosystems — ISBN: 978-81-69372-80-0. Pages: 381 - 408
The swift digital evolution of financial services has markedly heightened the need for safe, transparent, and efficient transaction systems. Conventional centralised financial systems frequently encounter issues including fraud, cyberattacks, data breaches, identity theft, and insufficient transparency. Blockchain technology has surfaced as a transformative solution that offers decentralised, unalterable, and tamper-proof transaction systems. Utilising cryptographic methods, distributed ledger systems, consensus protocols, and smart contracts, blockchain facilitates secure financial transactions and diminishes dependence on middlemen. This chapter offers an extensive examination of blockchain-based financial systems, including their structures, security protocols, applications, obstacles, and prospective research avenues within cloud-integrated IoT and e-commerce environments.
