• Ranking Fraud Detection for Mobile Apps: A Holistic View
• Securing the Deep Fraud Detector in Large-Scale E-Commerce Platform via Adversarial Machine Learning Approach
• Graph-Based User Behavior Modeling: From Prediction to Fraud Detection
• Exposing Search and Advertisement Abuse Tactics and Infrastructure of Technical Support Scammers
• HiDDen: Hierarchical Dense Subgraph Detection with Application to Financial Fraud Detection
• REV2: Fraudulent User Prediction in Rating Platforms
• Fraud Detection with Density Estimation Trees
• AI Technologies to Defeat Identity Theft Vulnerabilities
• A Machine-Learned Proactive Moderation System for Auction Fraud Detection
• Realtime Constrained Cycle Detection in Large Dynamic Graphs
• Using Co-Visitation Networks For Detecting Large Scale Online Display Advertising Exchange Fraud
• Crowd Fraud Detection in Internet Advertising
• Large Graph Mining: Patterns, Cascades, Fraud Detection, and Algorithms
• Online Modeling of Proactive Moderation System for Auction Fraud Detection
• Using Relational Knowledge Discovery to Prevent Securities Fraud
• NetProbe: A Fast and Scalable System for Fraud Detection in Online Auction Networks
• Identifying Anomalies in Graph Streams Using Change Detection
• Detecting Fraud in Health Insurance Data: Learning to Model Incomplete Benford's Law Distributions
• Key Player Identification in Underground Forums over Attributed Heterogeneous Information Network Embedding Framework
• Fraud Detection by Generating Positive Samples for Classification from Unlabeled Data
• PD-FDS: Purchase Density based Online Credit Card Fraud Detection System
• Improving Card Fraud Detection through Suspicious Pattern Discovery
• A graph-based, semi-supervised, credit card fraud detection system
• A Pattern Discovery Approach to Retail Fraud Detection
• FRAUDAR: Bounding Graph Fraud in the Face of Camouflage
• FARE: Schema-Agnostic Anomaly Detection in Social Event Logs
• Improving Credit Card Fraud Detection with Calibrated Probabilities
• Credit Card Fraud Detection Using Meta-Learning: Issues and Initial Results
• Robust System for Identifying Procurement Fraud
• BIRDNEST: Bayesian Inference for Ratings-Fraud Detection
• Document Classification and Visualisation to Support the Investigation of Suspected Fraud
• Detecting Fraudulent Personalities in Networks of Online Auctioneers
• FrauDetector: A Graph-Mining-based Framework for Fraudulent Phone Call Detection
• Toward Scalable Learning with Non-uniform Class and Cost Distributions: A Case Study in Credit Card Fraud Detection
• Toward An Intelligent Agent for Fraud Detection — The CFE Agent
• Uncovering Download Fraud Activities in Mobile App Markets
• No Place to Hide: Catching Fraudulent Entities in Tensors
• Detection of money laundering groups using supervised learning in networks
• Call-based Fraud Detection in Mobile Communication Networks using a Hierarchical Regime-Switching Model
• Impression Allocation for Combating Fraud in E-commerce Via Deep Reinforcement Learning with Action Norm Penalty
• Online Reputation Fraud Campaign Detection in User Ratings
• Catch the Black Sheep: Unified Framework for Shilling Attack Detection Based on Fraudulent Action Propagation
• Utility-Based Fraud Detection
• Graph Analysis for Detecting Fraud, Waste, and Abuse in Healthcare Data
• Anomaly, Event, and Fraud Detection in Large Network Datasets
• Fraudulent Support Telephone Number Identification Based on Co-occurrence Information on theWeb