Deep Secure Fraud in Banking Transactions

Deep Secure Fraud in Banking Transactions presents a comprehensive exploration of modern fraud detection techniques using advanced deep learning and secure computing approaches. As digital banking rapidly evolves, financial institutions face increasingly sophisticated cyber threats. This book addresses these challenges by integrating artificial intelligence, machine learning, and secure transaction protocols to identify and prevent fraudulent activities in real time. The authors provide detailed insights into fraud patterns, anomaly detection models, and secure system architectures tailored for banking environments. Practical case studies, algorithms, and implementation strategies are discussed to bridge the gap between theory and real-world application. Designed for researchers, academicians, and industry professionals, this book serves as a valuable resource for understanding and developing intelligent, secure, and scalable solutions to safeguard financial transactions in the digital era.

Dr. Shaik Akbar, Professor, CSE–Data Science Department, PSCMRCET, Vijayawada, with a Ph.D. and PDF in CSE, reflecting 22+ years of excellence in teaching, research, and administration. He has authored numerous journal papers, secured multiple patents, presented at conferences, and published several textbooks earning awards for academic contributions. As a project and PhD supervisor, he mentors and nurtures academic growth among students.