Big Data Security Governance and Prevention : Traffic Anti-Fraud in Practice

This book provides a practical reference for traffic anti-fraud, establishing a new standard for accessible, real-world traffic security governance that empowers readers to design scalable defenses while maintaining optimal user experience. The internet’s rapid growth has enabled a surge in digital fraud.Cybercriminals exploit every stage of online traffic, from fake promotion scams and bot-driven account fraud to "coupon hacking" during e-commerce sales and sophisticated phishing campaigns.These threats cost billions globally and demand urgent solutions to protect users and platforms.This practical guide demystifies traffic anti-fraud with a five-part, 12-chapter framework.It begins with foundational concepts and then dissects real-world fraud tactics.Part three focuses on data preparation and governance.Core chapters introduce cutting-edge tools, such as device fingerprinting, AI-powered anomaly detection, graph-based network analysis, and cross-modal threat fusion.The final section provides step-by-step strategies for building adaptive anti-fraud systems. This exceptional resource is ideal for cybersecurity professionals, developers, researchers, and students interested in cybercrime prevention, risk governance, and big data security.