Big Data Security Governance and Prevention Traffic Anti - Fraud in Practice
Big Data Security Governance and Prevention Traffic Anti - Fraud in Practice | 29.35 MB
Title: Big Data Security Governance and Prevention Traffic Anti - Fraud in Practice
Author: Zhang, Kai, Yang, Ze, Hao, Liyang, Xiong, Qi
Category: Computer Security, General Computing, Networking & Communications, Computer Science, Science & Technology
Language: English | 200 Pages | ISBN: 9781040972373
Description:
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.
DOWNLOAD:
https://rapidgator.net/file/2ceea8e6385b2310b690571a7e68a46a/Big_Data_Security_Governance_and_Prevention.rar
https://nitroflare.com/view/91A7E48A1F7116D/Big_Data_Security_Governance_and_Prevention.rar
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.
DOWNLOAD:
https://rapidgator.net/file/2ceea8e6385b2310b690571a7e68a46a/Big_Data_Security_Governance_and_Prevention.rar
https://nitroflare.com/view/91A7E48A1F7116D/Big_Data_Security_Governance_and_Prevention.rar
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