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ITPUB
ITPUB
Feb 22, 2026 · Backend Development

Designing a Cost‑Controlled “Cut‑One‑Knife” Promotion Engine for Massive Concurrency

This article breaks down the algorithm and architecture behind Pinduoduo's "cut‑one‑knife" promotion, explaining how dynamic pricing based on user value, Zeno’s paradox, Redis atomic operations, and anti‑fraud measures ensure users receive phones without the platform incurring losses even under massive traffic and bot attacks.

Zeno paradoxanti-frauddynamic pricing
0 likes · 8 min read
Designing a Cost‑Controlled “Cut‑One‑Knife” Promotion Engine for Massive Concurrency
DataFunSummit
DataFunSummit
Dec 30, 2025 · Artificial Intelligence

How Large Models Are Revolutionizing Anti‑Fraud Detection: Fusion, Script Recognition, and Automated Iteration

This article examines how a major internet platform leverages large‑model AI—through multimodal fusion, script‑recognition fine‑tuning, and an automatic model‑iteration framework—to overcome precision, adversarial, and cross‑scenario challenges in fraud detection, and how agent‑based tools further boost operational efficiency.

Model Iterationagent automationanti-fraud
0 likes · 24 min read
How Large Models Are Revolutionizing Anti‑Fraud Detection: Fusion, Script Recognition, and Automated Iteration
Baidu Geek Talk
Baidu Geek Talk
Jun 18, 2025 · Artificial Intelligence

How Graph Algorithms Power Anti‑Fraud in Marketing and E‑Commerce

This article explores how black‑market cheating in marketing campaigns and e‑commerce is detected using graph‑based techniques such as same‑person mining, label propagation, Fraudar, and GCN models, and discusses future directions like multimodal data fusion and real‑time dynamic graph computation.

FraudarGCNRisk Detection
0 likes · 18 min read
How Graph Algorithms Power Anti‑Fraud in Marketing and E‑Commerce
DeWu Technology
DeWu Technology
Apr 21, 2025 · Backend Development

Design and Evolution of a Unified Exchange Mall Middleware Platform

The unified exchange mall middleware platform consolidates disparate points‑redemption and lottery flows into a four‑layer architecture—business, gameplay templates, domain models, and downstream services—offering standardized APIs, dynamic RPC routing, Redis‑based inventory control, anti‑fraud safeguards, and built‑in monitoring, thereby cutting development costs, enhancing maintainability, and ensuring system stability.

BackendGolangMicroservices
0 likes · 18 min read
Design and Evolution of a Unified Exchange Mall Middleware Platform
Baobao Algorithm Notes
Baobao Algorithm Notes
Apr 15, 2025 · Industry Insights

Why GLM‑Z1‑AirX Hits 150‑200 TPS: A Deep Dive into LLM Speed Benchmarking

The article examines the slowdown caused by long‑chain‑of‑thought LLMs, presents a Python benchmarking script, compares token‑per‑second performance of several models—including the ultra‑fast GLM‑Z1‑AirX—and demonstrates a real‑time anti‑fraud use case that benefits from sub‑second response times.

BenchmarkGLM-Z1-AirXLLM
0 likes · 13 min read
Why GLM‑Z1‑AirX Hits 150‑200 TPS: A Deep Dive into LLM Speed Benchmarking
Baidu Tech Salon
Baidu Tech Salon
Mar 6, 2025 · Big Data

Real-Time Anti-Fraud Streaming System Based on Flink: Architecture, Challenges, and Optimizations

The article describes a Flink‑based real‑time anti‑fraud streaming system that combines a risk‑control platform, configurable YAML‑driven pipelines, and optimized state handling—using early event‑time triggers, micro‑batch caching, and coarse‑grained key reduction—to compute multi‑dimensional features, support rapid strategy updates, simulation filtering, and seamless output to ClickHouse, Hive, and Redis for both instant monitoring and offline analysis.

ConfigurationFlinkReal-time Streaming
0 likes · 26 min read
Real-Time Anti-Fraud Streaming System Based on Flink: Architecture, Challenges, and Optimizations
Baidu Geek Talk
Baidu Geek Talk
Dec 18, 2024 · Artificial Intelligence

GEE Graph Embedding Algorithm for Business Security Anomaly Detection

The article presents the GEE (Graph Encoder Embedding) algorithm for business security anomaly detection, explains its label‑propagation foundation, evaluates it on ten‑million‑edge real data, identifies inefficiencies in the original implementation, and demonstrates that vectorized NumPy/Pandas optimizations reduce runtime from 55 seconds to about 4 seconds while preserving meaningful TSNE‑visualized embeddings.

GEE algorithmanomaly detectionanti-fraud
0 likes · 21 min read
GEE Graph Embedding Algorithm for Business Security Anomaly Detection
Alimama Tech
Alimama Tech
Nov 13, 2024 · Artificial Intelligence

DeepString: Alibaba's Anti‑Fraud Platform Using Large Models for Real‑Time Traffic Detection

Alibaba's anti-fraud platform DeepString uses large unsupervised models to detect abnormal traffic in real time across multiple advertising products, combining a foundation model for event mining, anomaly measurement, and an alignment model for online filtering, reducing reliance on manual labeling and domain expertise.

algorithm frameworkanti-fraudlarge models
0 likes · 19 min read
DeepString: Alibaba's Anti‑Fraud Platform Using Large Models for Real‑Time Traffic Detection
DataFunSummit
DataFunSummit
May 28, 2024 · Information Security

OPPO Application Distribution Anti‑Fraud Practices and Countermeasure Architecture

This article presents a comprehensive overview of OPPO's application distribution platform, detailing the black‑gray‑market threats it faces, the multi‑layered anti‑fraud architecture—including perception, identification, evaluation, and disposal modules—and real‑world case studies that demonstrate the effectiveness of its traffic anti‑cheat tools.

App DistributionOPPOSecurity
0 likes · 17 min read
OPPO Application Distribution Anti‑Fraud Practices and Countermeasure Architecture
DataFunSummit
DataFunSummit
Apr 6, 2024 · Information Security

Comprehensive Guide to Malicious Website Anti‑Fraud: Detection, Operation, and Modeling

This article provides a detailed overview of malicious website anti‑fraud, covering classification, development, operational tactics, revenue models, multi‑dimensional anomaly detection, and advanced counter‑measure models such as fingerprint, text, image, complex network, and multimodal approaches.

Graph Neural Networkanomaly detectionanti-fraud
0 likes · 16 min read
Comprehensive Guide to Malicious Website Anti‑Fraud: Detection, Operation, and Modeling
ZhongAn Tech Team
ZhongAn Tech Team
Oct 20, 2023 · Artificial Intelligence

Document Analytics & Anti‑Fraud Support Platform for Hong Kong Virtual Banking

This article describes the design and implementation of a Document Analytics & Anti‑Fraud Support platform for Hong Kong virtual banking, detailing its OCR/NLP‑driven pipeline, dynamic rule engine, multi‑template PDF processing, model training, and the resulting improvements in fraud detection and operational efficiency.

NLPOCRanti-fraud
0 likes · 18 min read
Document Analytics & Anti‑Fraud Support Platform for Hong Kong Virtual Banking
AntTech
AntTech
Oct 8, 2023 · Information Security

International Standards for Intelligent Device Risk Control: IEEE DTX Architecture and ITU Anti‑Fraud Guidelines

The article explains how recent IEEE and ITU international standards introduce a Device Trust Extension (DTX) framework and anti‑fraud detection guidelines for intelligent terminals, highlighting China's leadership, the technical content of the standards, and Ant Group's large‑scale deployment to enhance device security and risk management.

DTXIEEE StandardITU
0 likes · 5 min read
International Standards for Intelligent Device Risk Control: IEEE DTX Architecture and ITU Anti‑Fraud Guidelines
Efficient Ops
Efficient Ops
Sep 24, 2023 · Information Security

How China Postal Savings Bank Built an Enterprise‑Level AI‑Powered Anti‑Fraud Platform

The 2023 China International Service Trade Fair’s Digital Transformation Forum showcased the Postal Savings Bank’s enterprise‑grade intelligent anti‑fraud platform, detailing its stream‑batch integration, graph‑based AI models, and multi‑layer risk‑control architecture that safeguards millions of daily transactions across retail, agricultural, and credit services.

China Postal Savings Bankanti-fraudstream processing
0 likes · 8 min read
How China Postal Savings Bank Built an Enterprise‑Level AI‑Powered Anti‑Fraud Platform
DataFunTalk
DataFunTalk
Aug 7, 2023 · Information Security

Design and Exploration of Mobile Game Anti‑Fraud Systems

This article examines the mobile gaming black‑market ecosystem, outlines common fraud patterns, and presents a comprehensive anti‑fraud architecture—including real‑time and offline risk assessment, entity profiling, and mitigation strategies—while sharing practical insights and lessons learned from implementation.

Game SecurityMobile Gaminganti-fraud
0 likes · 19 min read
Design and Exploration of Mobile Game Anti‑Fraud Systems
vivo Internet Technology
vivo Internet Technology
Jun 14, 2023 · Information Security

Vivo Game Anti-Cheat Analysis: Identifying and Combating Black Market Fraud

The article examines Vivo’s gaming platform’s fight against black‑market fraud, outlining profit motives, types of illicit activities, brushing techniques, and the company’s three‑stage anti‑fraud framework—pre‑risk perception, in‑process detection, and post‑strike closure—illustrated with two real‑world case studies.

Game SecurityVivo platformanti-fraud
0 likes · 13 min read
Vivo Game Anti-Cheat Analysis: Identifying and Combating Black Market Fraud
DataFunTalk
DataFunTalk
Mar 25, 2023 · Artificial Intelligence

ZhongAn Financial Real‑Time Feature Platform: MLOps Practices, Architecture and Anti‑Fraud Applications

This article presents ZhongAn Financial’s end‑to‑end MLOps workflow and real‑time feature platform architecture, detailing team roles, data pipelines, Flink‑based processing, TableStore storage, anti‑fraud feature design, and answers to common implementation questions, offering a comprehensive guide for building scalable, low‑latency ML services in finance.

FlinkMLOpsTablestore
0 likes · 25 min read
ZhongAn Financial Real‑Time Feature Platform: MLOps Practices, Architecture and Anti‑Fraud Applications
vivo Internet Technology
vivo Internet Technology
Feb 15, 2023 · Information Security

Ad Traffic Anti‑Fraud: Algorithms, System Architecture, and Case Studies

The article explains how ad traffic fraud—ranging from simulated impressions to click farms—can be combated using a four‑layer risk‑control system that leverages unsupervised (DBSCAN, Isolation Forest) and supervised (Logistic Regression, Random Forest) algorithms, detailing data pipelines, model training, monitoring, and real‑world case studies.

Ad FraudAdvertisingRisk Detection
0 likes · 15 min read
Ad Traffic Anti‑Fraud: Algorithms, System Architecture, and Case Studies
AntTech
AntTech
Jan 9, 2023 · Artificial Intelligence

Overview of the Financial Big Data Anti‑Fraud Technology Whitepaper

This article introduces the Ant Group and Tsinghua University’s Financial Big Data Anti‑Fraud Technology Whitepaper, outlining the new legal context, fraud characteristics, and a three‑stage detection framework that leverages multi‑dimensional graphs, trustworthy AI, and data security to improve pre‑, during‑, and post‑transaction risk management.

AIanti-fraudfinancial data
0 likes · 9 min read
Overview of the Financial Big Data Anti‑Fraud Technology Whitepaper
Xiaohongshu Tech REDtech
Xiaohongshu Tech REDtech
Nov 30, 2022 · Information Security

Best Practices for Community and E‑commerce Fraud Prevention on Xiaohongshu: Understanding and Combating Fake Traffic

The article outlines Xiaohongshu’s comprehensive anti‑fraud strategy—defining fake traffic, exposing three service‑provider models, detailing identification and governance challenges, and recommending engine‑based risk‑control, a five‑step process, and AI‑driven behavior, clustering, and graph analyses that have already eliminated billions of fraudulent likes.

anti-fraude-commerce securityfraud detection
0 likes · 22 min read
Best Practices for Community and E‑commerce Fraud Prevention on Xiaohongshu: Understanding and Combating Fake Traffic
DataFunSummit
DataFunSummit
Nov 25, 2022 · Information Security

Black and Gray Market Threats and Countermeasures in the Residential Services Industry

This article presents a comprehensive analysis of black‑gray market activities in the residential services sector, detailing industry service models, typical fraud scenarios, intelligence‑gathering architecture, traceability capabilities, and multi‑stage counter‑measure processes aimed at detection, investigation, and prosecution.

Intelligenceanti-fraudblack market
0 likes · 11 min read
Black and Gray Market Threats and Countermeasures in the Residential Services Industry
Xiaohongshu Tech REDtech
Xiaohongshu Tech REDtech
Sep 22, 2022 · Big Data

Graph Computing Algorithms for E‑commerce Anti‑Fraud and Reselling Bot Detection

The Xiaohongshu anti‑fraud team combats sophisticated same‑group and crowdsourced reselling bots by ingesting real‑time transaction streams into a Nebula Graph, using multi‑hop sub‑graph sampling, label propagation, and modularity‑based community detection to identify suspicious clusters, update risk pools, and enforce personalized purchase‑limit rules.

Big Dataanti-fraudbot detection
0 likes · 9 min read
Graph Computing Algorithms for E‑commerce Anti‑Fraud and Reselling Bot Detection
Baidu Geek Talk
Baidu Geek Talk
Aug 16, 2022 · Artificial Intelligence

Louvain Algorithm for Community Detection in Anti‑Fraud Systems

The Louvain algorithm, a fast modularity‑maximizing community‑detection method, iteratively merges nodes into hierarchical super‑nodes, enabling anti‑fraud systems to uncover hidden collusive groups in weighted transaction graphs, thereby improving detection of fake orders, coupon abuse, and other illicit behaviors despite its iterative nature and streaming limitations.

anti-fraudcommunity-detectiongraph algorithms
0 likes · 10 min read
Louvain Algorithm for Community Detection in Anti‑Fraud Systems
AntTech
AntTech
Jul 12, 2022 · Artificial Intelligence

AI Visual Anti‑Fraud Model Battles QR Code Abuse in the Beverage Industry

The article describes how Ant Group's AI visual anti‑fraud system, built by vision engineers, combats large‑scale QR‑code fraud targeting beverage bottle caps, detailing the black‑gray industry's tactics, the model's rapid detection capabilities, continuous unsupervised learning upgrades, and its broader applications in remote‑sensing and risk management.

AIImage ProcessingQR code
0 likes · 13 min read
AI Visual Anti‑Fraud Model Battles QR Code Abuse in the Beverage Industry
DataFunTalk
DataFunTalk
Jun 21, 2022 · Information Security

Trusted Traffic Governance and Anti‑Fraud Strategies Using Captcha

This talk explains how to use semantic-driven captcha mechanisms to classify and manage trusted versus untrusted traffic, detailing anti‑fraud strategies, flow identification, countermeasures against simulator and protocol cracking, and proactive updates to stay ahead of black‑market attacks.

CaptchaTraffic Classificationadversarial attacks
0 likes · 15 min read
Trusted Traffic Governance and Anti‑Fraud Strategies Using Captcha
AntTech
AntTech
May 30, 2022 · Information Security

Ant Group’s Technical Innovations: Green Computing, Trusted Mobile Anti‑Fraud Sandbox, Open‑Source Privacy Platform, OceanBase DB Competition, and Security Parallel Slice

This article highlights Ant Group’s recent technical achievements—including green carbon‑reduction scheduling, the AntDTX trusted privacy sandbox for mobile anti‑fraud, the open‑source YinYu privacy‑computing platform, the OceanBase database competition, and the Space5D security parallel‑slice architecture—showcasing their impact on sustainability, security, and open‑source collaboration.

Cloud NativePrivacy Computinganti-fraud
0 likes · 9 min read
Ant Group’s Technical Innovations: Green Computing, Trusted Mobile Anti‑Fraud Sandbox, Open‑Source Privacy Platform, OceanBase DB Competition, and Security Parallel Slice
Baidu Intelligent Testing
Baidu Intelligent Testing
Oct 19, 2021 · Artificial Intelligence

Graph-Based Anti-Fraud: Gang Mining and Node Representation for Account Security

This article describes how Baidu's account security team leverages large‑scale graph technology and graph neural networks to detect and characterize black‑industry cheating gangs, presents a customized GraphSAGE link‑prediction model, and evaluates its superiority over MLP and GCN embeddings for downstream risk‑control tasks.

Node Representationanti-fraudgraph neural networks
0 likes · 12 min read
Graph-Based Anti-Fraud: Gang Mining and Node Representation for Account Security
DataFunSummit
DataFunSummit
Oct 8, 2021 · Artificial Intelligence

Graph Computing for Financial Credit Risk Control and Anti‑Fraud: Architecture, Challenges, and Lessons Learned

This article examines how graph computing is applied to financial credit risk management and anti‑fraud, covering business background, key credit terminology, stakeholder roles, graph‑based fraud detection techniques, system architecture evolution across three development stages, practical requirements such as stability, timeliness, accuracy and controllability, and summarizes operational insights.

AIanti-fraudgraph computing
0 likes · 16 min read
Graph Computing for Financial Credit Risk Control and Anti‑Fraud: Architecture, Challenges, and Lessons Learned
Baidu Geek Talk
Baidu Geek Talk
Sep 29, 2021 · Artificial Intelligence

Graph-Based Anti-Fraud: Gang Mining and Node Representation Using Graph Neural Networks

To curb large‑scale, organized fraud on Baidu’s platform, the Account Security team built a scalable heterogeneous graph framework that links accounts, features, and devices, trains GraphSAGE‑based node embeddings via link‑prediction, and leverages these representations to uncover fraud gangs, boosting detection accuracy above 90% across billions of nodes.

anti-fraudgraph mininggraph neural networks
0 likes · 13 min read
Graph-Based Anti-Fraud: Gang Mining and Node Representation Using Graph Neural Networks
DataFunTalk
DataFunTalk
Aug 21, 2021 · Information Security

CAPTCHA: History, Development, and Its Role in Cybersecurity and Anti‑Fraud Strategies

This article reviews the origin and evolution of CAPTCHAs, examines early applications and OCR attacks, describes the three generations of reCAPTCHA and emerging verification methods, and discusses how CAPTCHAs are used to raise attack barriers, filter malicious traffic, and support risk assessment in modern anti‑fraud systems.

AICaptchaSecurity
0 likes · 13 min read
CAPTCHA: History, Development, and Its Role in Cybersecurity and Anti‑Fraud Strategies
58 Tech
58 Tech
May 10, 2021 · Information Security

Marketing Anti‑Fraud Algorithm Framework and Practice at 58.com

This article details the design, implementation, and evaluation of a multi‑layer anti‑fraud system for 58.com’s marketing activities, covering data and feature engineering, unsupervised and supervised models, graph‑based community detection, and semi‑supervised graph neural networks, with empirical results demonstrating their effectiveness.

Graph Neural NetworkMarketingUnsupervised Learning
0 likes · 18 min read
Marketing Anti‑Fraud Algorithm Framework and Practice at 58.com
NetEase Smart Enterprise Tech+
NetEase Smart Enterprise Tech+
Mar 9, 2021 · Information Security

How Server‑Side Device Fingerprinting Boosts Security and Stability

Device fingerprinting uniquely identifies devices using collected data; this article explains how uniqueness and stability are measured, shows probability‑based calculations for single and combined fields, discusses the shortcomings of client‑side methods, and details a server‑side multi‑algorithm approach that improves security and stability.

Securityanti-frauddecision tree
0 likes · 11 min read
How Server‑Side Device Fingerprinting Boosts Security and Stability
DataFunTalk
DataFunTalk
Jan 31, 2021 · Artificial Intelligence

Applying Graph Algorithms and Graph Convolutional Networks for Advertising Anti‑Fraud at 58.com

This article explains how various graph algorithms—including connected components, label propagation, Louvain community detection, and Graph Convolutional Networks—are built on large‑scale user‑behavior graphs using Spark GraphX to detect and mitigate advertising fraud, detailing methodology, implementation, and experimental results.

GCNSpark GraphXanti-fraud
0 likes · 13 min read
Applying Graph Algorithms and Graph Convolutional Networks for Advertising Anti‑Fraud at 58.com
DataFunTalk
DataFunTalk
Jan 28, 2021 · Big Data

Real-Time Financial Data Lake: Architecture, Practices, and Applications at Zhongyuan Bank

This talk by Ba Xueyu, a senior big data platform engineer at Zhongyuan Bank, outlines the background, architecture, and engineering practices of a real‑time financial data lake, highlighting its open, timely, and integrated design, streaming platform implementation, and use cases such as anti‑fraud and real‑time BI.

Flinkanti-fraudfinancial analytics
0 likes · 15 min read
Real-Time Financial Data Lake: Architecture, Practices, and Applications at Zhongyuan Bank
Alibaba Cloud Developer
Alibaba Cloud Developer
Dec 16, 2020 · Artificial Intelligence

How to Detect and Prevent Advertising Fraud with Advanced AI Techniques

This article explains the scale of online ad fraud, outlines common advertising billing models, describes how fake traffic generates revenue, defines invalid clicks, and presents a comprehensive anti‑fraud system that combines rule‑based methods, feature engineering, and AI models such as TextCNN, BiLSTM, BERT, Wide&Deep and GraphSage to identify and block fraudulent ad clicks.

AIAd FraudAdvertising
0 likes · 33 min read
How to Detect and Prevent Advertising Fraud with Advanced AI Techniques
58 Tech
58 Tech
Nov 18, 2020 · Artificial Intelligence

Applying Graph Algorithms and Graph Convolutional Networks to Advertising Anti‑Fraud

This article describes how graph theory and graph convolutional neural networks are leveraged to model user‑IP relationships, detect fraudulent advertising clusters, and improve detection accuracy and recall through a combination of unsupervised graph algorithms and supervised GCN training in a large‑scale ad‑anti‑fraud system.

AdvertisingGCNSpark GraphX
0 likes · 14 min read
Applying Graph Algorithms and Graph Convolutional Networks to Advertising Anti‑Fraud
JD Tech Talk
JD Tech Talk
Aug 21, 2020 · Artificial Intelligence

JD Digits' Intelligent Anti‑Fraud Platform: AI‑Driven Real‑Time Fraud Detection and Knowledge‑Graph Solutions

JD Digits' intelligent anti‑fraud platform leverages machine learning, big‑data processing, graph neural networks and small‑sample knowledge‑graph algorithms to provide millisecond‑level, real‑time protection across 600+ scenarios, while also offering AI‑powered solutions to banks and publishing research at top conferences.

AIGraph Neural NetworkKnowledge Graph
0 likes · 6 min read
JD Digits' Intelligent Anti‑Fraud Platform: AI‑Driven Real‑Time Fraud Detection and Knowledge‑Graph Solutions
DataFunTalk
DataFunTalk
Jun 22, 2020 · Artificial Intelligence

Ctrip's Automated Iterative Anti‑Fraud Modeling Framework for Payment Risk

The article describes Ctrip's payment fraud risk characteristics, a comprehensive automated iterative anti‑fraud model framework—including variable system, GAN‑augmented sample generation, RNN behavior encoding, and tree‑based classifiers—and demonstrates how this approach restores recall performance compared with traditional static models.

GANRNNRisk Modeling
0 likes · 12 min read
Ctrip's Automated Iterative Anti‑Fraud Modeling Framework for Payment Risk
JD Tech Talk
JD Tech Talk
Mar 16, 2020 · Artificial Intelligence

JD Digits' Self‑Developed Intelligent Anti‑Fraud Platform and AI‑Powered Account Security Guarantee

JD Digits explains how its AI‑driven anti‑fraud platform, featuring automatic adversarial machine learning and graph neural networks, underpins a new one‑million‑yuan account security guarantee that proactively protects users from invisible financial fraud while improving the overall user experience.

AIGraph Neural Networkaccount security
0 likes · 10 min read
JD Digits' Self‑Developed Intelligent Anti‑Fraud Platform and AI‑Powered Account Security Guarantee
Qunar Tech Salon
Qunar Tech Salon
Aug 29, 2019 · Information Security

Using Graph Databases for Fraud Detection in Ride‑Hailing Platforms

The article explains how building a Neo4j‑based social graph of users, drivers, devices and other attributes enables detection of individual and group subsidy‑abuse fraud in ride‑hailing services through multi‑hop relationship analysis and targeted rule‑based alerts.

Neo4jRide HailingSocial Network Analysis
0 likes · 6 min read
Using Graph Databases for Fraud Detection in Ride‑Hailing Platforms
DataFunTalk
DataFunTalk
Apr 17, 2019 · Artificial Intelligence

Evolution of Ctrip Financial Risk Control Models: From Data Platform to AI‑Driven Scoring and Anti‑Fraud Systems

This report details Ctrip Financial's end‑to‑end risk control development, covering business overview, a three‑layer data platform, the progression of credit scoring and anti‑fraud models from rule‑based to advanced AI techniques, and the evaluation, monitoring, and social‑network‑based fraud detection strategies employed.

Big DataFinancial AIRisk Modeling
0 likes · 16 min read
Evolution of Ctrip Financial Risk Control Models: From Data Platform to AI‑Driven Scoring and Anti‑Fraud Systems
iQIYI Technical Product Team
iQIYI Technical Product Team
Nov 2, 2018 · Artificial Intelligence

iQIYI Tech Salon Session 3 (Beijing): AI Technology Practices and Applications

The third iQIYI Tech Salon in Beijing, held despite strong winds, showcased five expert talks on AI‑driven video library management, NLP for entertainment content, AI‑based video encoding, traffic anti‑fraud systems, and short‑video personalized recommendation, illustrating AI’s impact on content creation, quality, security, and user experience.

AINLPRecommendation Systems
0 likes · 5 min read
iQIYI Tech Salon Session 3 (Beijing): AI Technology Practices and Applications
DataFunTalk
DataFunTalk
Oct 17, 2018 · Artificial Intelligence

Design Principles for AI‑Driven Anti‑Fraud Systems

The article outlines Tongdun Technology's anti‑fraud challenges, presents their AI‑based detection solutions, and details design principles—including early warning, multi‑feature analysis, and human‑machine collaboration—to build a robust, multi‑layered fraud prevention framework.

AI designRisk DetectionUnsupervised Learning
0 likes · 10 min read
Design Principles for AI‑Driven Anti‑Fraud Systems
JD Tech
JD Tech
Sep 14, 2018 · Information Security

AI Explainability and Deep Learning Techniques for Security: JD Security’s Recent Research Highlights

JD Security presents a series of AI‑driven security innovations—including black‑box explanation methods, deep‑learning crash analysis, AI‑vs‑AI e‑commerce fraud defenses, and open‑source collaboration—to illustrate how artificial intelligence can be made transparent, effective, and safely integrated into modern security operations.

AIanti-fraudcrash analysis
0 likes · 7 min read
AI Explainability and Deep Learning Techniques for Security: JD Security’s Recent Research Highlights
DataFunTalk
DataFunTalk
Aug 21, 2018 · Artificial Intelligence

iQIYI Traffic Anti-Cheat: Techniques, System Architecture, and Future Directions

This article provides a comprehensive overview of iQIYI's traffic anti‑cheat mechanisms, covering definitions of fraudulent traffic, industry challenges, data cleaning relationships, system design, rule‑based and machine‑learning solutions, feature engineering, model evaluation, monitoring, service applications, and future prospects.

Big DataSystem ArchitectureTraffic analysis
0 likes · 11 min read
iQIYI Traffic Anti-Cheat: Techniques, System Architecture, and Future Directions
Architecture Digest
Architecture Digest
May 25, 2018 · Backend Development

Modular Design, Service Extraction, and High‑Concurrency Optimization Practices for Backend Development

This article explains how modular design and service extraction can reduce system complexity and improve reusability, illustrates practical before‑and‑after examples for red‑packet and notification services, and details high‑concurrency techniques such as caching, asynchronous processing, rate limiting, service degradation, anti‑fraud measures, and concurrency‑safe database operations.

Backend Architectureanti-fraudcaching
0 likes · 13 min read
Modular Design, Service Extraction, and High‑Concurrency Optimization Practices for Backend Development
ITPUB
ITPUB
Nov 12, 2017 · Information Security

How E‑commerce Platforms Fight Double‑11 Fraud: Inside NetEase’s Anti‑Cheat Architecture

This article examines the rise of organized “wool‑pulling” fraud groups during China’s Double‑11 shopping festival, outlines their tools and tactics, and details NetEase Cloud Security’s multi‑layered anti‑fraud system—including captcha, SMS verification, IP rules, device fingerprinting, rule engines, user profiling, network graph analysis, and blacklist strategies—to protect e‑commerce platforms.

Double 11anti-fraude‑commerce
0 likes · 16 min read
How E‑commerce Platforms Fight Double‑11 Fraud: Inside NetEase’s Anti‑Cheat Architecture
Alibaba Cloud Developer
Alibaba Cloud Developer
Sep 13, 2016 · Artificial Intelligence

How Game Theory and AI Stop Fake Reviews on E‑Commerce Platforms

This article explains how Alibaba combines big‑data analytics, machine learning, and mechanism‑design game theory to create a recommendation system that removes incentives for merchants to generate fake orders, improving fairness and user experience on e‑commerce platforms.

Game TheoryRecommendation Systemsanti-fraud
0 likes · 3 min read
How Game Theory and AI Stop Fake Reviews on E‑Commerce Platforms
ITPUB
ITPUB
Jun 11, 2016 · Big Data

How 58 Daojia Leverages User Portraits to Boost Operations and Fight Fraud

This article details 58 Daojia's data‑driven approach to building user‑portrait tags, covering tag construction, evaluation, and practical applications such as personalized recommendations, anti‑fraud measures, coupon distribution, and dynamic pricing, while outlining the underlying big‑data architecture and technical challenges.

Big Dataanti-frauddata mining
0 likes · 18 min read
How 58 Daojia Leverages User Portraits to Boost Operations and Fight Fraud
21CTO
21CTO
Mar 16, 2016 · Big Data

Inside Uber’s Tech: How Data, AI, and Cloud Power Ride‑Sharing in China

Uber’s CTO Thuan Pham revealed at a Chinese tech salon how the company’s global architecture, data‑center strategy, cloud partnership with Baidu, anti‑fraud machine‑learning models, map localization and big‑data analytics together enable a unified yet locally adapted ride‑sharing platform across China and the world.

Big DataTechnology ArchitectureUber
0 likes · 17 min read
Inside Uber’s Tech: How Data, AI, and Cloud Power Ride‑Sharing in China
21CTO
21CTO
Dec 7, 2015 · Information Security

How Tencent Combats Fraudsters with Big Data and AI‑Powered Risk Engines

This article explains how Tencent uses big‑data collection, user profiling, and AI‑driven risk learning engines to detect and block malicious accounts, proxy IPs, and fraudulent activities across e‑commerce and other platforms, detailing the architecture, algorithms, and practical defenses employed.

Big Dataanti-fraudfraud detection
0 likes · 14 min read
How Tencent Combats Fraudsters with Big Data and AI‑Powered Risk Engines
High Availability Architecture
High Availability Architecture
Aug 5, 2015 · Big Data

DSP Advertising System Architecture and Key Technologies

This article presents a comprehensive overview of DSP advertising system architecture, covering real‑time bidding infrastructure, audience targeting, data processing pipelines using Hadoop, Spark and Storm, click‑through‑rate prediction models, and anti‑fraud mechanisms, offering practical insights for engineers building high‑performance ad platforms.

Ad TechDSPanti-fraud
0 likes · 24 min read
DSP Advertising System Architecture and Key Technologies