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

di Kai Zhang (Autore)

Ze Yang (Autore)

Liyang Hao (Autore)

Taylor & Francis Ltd, 2026

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 an 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 12-chapter framework. It begins with foundational concepts and then dissects real-world fraud tactics, then 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 chapter 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.

• Autore: Kai Zhang, Ze Yang, Liyang Hao
• Editore: Taylor & Francis Ltd
• Collana: Data Communication Series
• Anno: 2026
• Rilegatura: Hardback
• Pagine: 224 p.
• Dimensioni: 254 x 178 mm
• EAN: 9781041255352

Testo in English