1st Edition

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

By Kai Zhang, Ze Yang, Liyang Hao, Qi Xiong Copyright 2027
224 Pages 178 B/W Illustrations
by CRC Press

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... Read more

1. Introduction  2. Traffic Fraud Tactics and Their Impact  3. Traffic Data Governance and Feature Engineering  4. Device Fingerprinting Technology  5. CAPTCHA Verification  6. Rules Engine  7. Countermeasures Against Machine Learning  8. Complex Network Adversarial Solutions  9. Multimodal Integrated Adversarial Solutions  10. New Adversarial Approaches  11. Operational System  12. Knowledge and Intelligence Mining and Applications

Biography

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.