Big Data Security Governance and Prevention: Traffic Anti-Fraud in Practice
暫譯: 大數據安全治理與防範：實務中的流量反詐騙
Zhang, Kai, Yang, Ze, Hao, Liyang
- 出版商: CRC
- 出版日期: 2026-09-29
- 售價: $3,830
- 貴賓價: 9.5 折 $3,638
- 語言: 英文
- 頁數: 188
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1041255357
- ISBN-13: 9781041255352
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相關分類:
大數據 Big-data
尚未上市，無法訂購
商品描述
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 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.
商品描述(中文翻譯)
這本書提供了一個實用的參考資料，針對流量反詐騙，建立了一個新的標準，以便於可接觸的、現實世界的流量安全治理，讓讀者能夠設計可擴展的防禦措施，同時保持最佳的用戶體驗。
隨著互聯網的快速增長，數位詐騙也隨之激增。網路犯罪分子利用在線流量的每一個階段，從虛假促銷詐騙和機器人驅動的帳戶詐騙，到電子商務銷售期間的「優惠券駭客」和複雜的釣魚攻擊。這些威脅在全球造成數十億的損失，迫切需要解決方案來保護用戶和平台。本實用指南以五個部分、12個章節的框架來揭開流量反詐騙的神秘面紗。它從基礎概念開始，然後剖析現實世界的詐騙策略。第三部分專注於數據準備和治理。核心章節介紹了尖端工具，如設備指紋識別、人工智慧驅動的異常檢測、基於圖形的網絡分析和跨模態威脅融合。最後一部分提供了逐步的策略，用於建立自適應的反詐騙系統。
這本卓越的資源非常適合對網路犯罪預防、風險治理和大數據安全感興趣的網路安全專業人士、開發者、研究人員和學生。
作者簡介
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.
作者簡介(中文翻譯)
張凱是騰訊的首席工程師，擁有超過十年的打擊網路犯罪經驗。他曾主導遊戲安全保護、金融風險控制系統和反詐騙架構的安全專案。他的核心專長在於大數據安全威脅建模。
楊澤是騰訊的研究員，專注於金融風險治理。他開發了基於人工智慧的機制，以應對支付生態系統中的地下經濟威脅。
郝立揚是騰訊的研究員，專注於行為安全系統。他為社交支付場景設計了即時賭博/詐騙干預引擎。
熊琦是騰訊的首席工程師，擁有15年的安全架構經驗。他主導了針對金融科技應用和移動生態系統的合規驅動安全解決方案。
