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.



Autorentext

Kai Zhang is a principal engineer at Tencent with over a decade of experience in combating cybercrimes. He has led security projects in game security protection, financial risk control systems, and anti-fraud architectures. His core expertise lies in big data security threat modeling.

Ze Yang is a researcher at Tencent dedicated to financial risk governance. He has developed AI-powered mechanisms to combat underground economy threats in payment ecosystems.

Liyang Hao is a researcher at Tencent focusing on behavioral security systems. He has designed real-time gambling/fraud intervention engines for social payment scenarios.

Qi Xiong is a principal engineer at Tencent with 15 years of experience in security architecture. He has spearheaded compliance-driven security solutions for fintech applications and mobile ecosystems.

Titel
Big Data Security Governance and Prevention
Untertitel
Traffic Anti-Fraud in Practice
EAN
9781040972335
Format
PDF
Veröffentlichung
29.09.2026
Digitaler Kopierschutz
frei
Anzahl Seiten
200