Knygos.lt nariams
Knygos.lt nariams
- Planuojame turėti už 98 d.
/https://libri-media.knygos-static.lt/591949f1-c7df-46af-8ad4-5592564f4ebb/1)
- Autorius: Kai Zhang, Liyang Hao, Qi Xiong, Ze Yang
- Leidėjas: Taylor & Francis Ltd
- Metai: 2026
- Puslapiai: 224
- ISBN-10: 1041255357
- ISBN-13: 9781041255352
- Kalba: Anglų
Big Data Security Governance and Prevention (el. knyga) (skaityta knyga) | knygos.lt
Atsiliepimai
Aprašymas
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.
- Autorius: Kai Zhang, Liyang Hao, Qi Xiong, Ze Yang
- Leidėjas: Taylor & Francis Ltd
- Metai: 2026
- Puslapiai: 224
- ISBN-10: 1041255357
- ISBN-13: 9781041255352
- Kalba: Anglų
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.
Atsiliepimai