Awesome Fraud Detection Research Papers.

A curated list of fraud detection papers from the following conferences:

• Network Science
• ASONAM
• COMPLEX NETWORKS
• Data Science
• DSAA
• Natural Language Processing
• ACL
• Data Mining
• KDD
• ICDM
• SIGIR
• SDM
• WWW
• CIKM
• Artificial Intelligence
• AAAI
• AISTATS
• IJCAI
• UAI
• Databases
• VLDB

Similar collections about graph classification, classification/regression tree, gradient boosting, Monte Carlo tree search, and community detection papers with implementations.

2025

• Global Attribute-Association Pattern Aggregation for Graph Fraud Detection (AAAI 2025)
• Mingjiang Duan, Da He, Tongya Zheng, Lingxiang Jia, Mingli Song, Xinyu Wang, Zunlei Feng

• [Paper]

• Context-aware Graph Neural Network for Graph-based Fraud Detection with Extremely Limited Labels (AAAI 2025)

• Pengbo Li, Hang Yu, Xiangfeng Luo

• [Paper]

• A Label-free Heterophily-guided Approach for Unsupervised Graph Fraud Detection (AAAI 2025)

• Junjun Pan, Yixin Liu, Xin Zheng, Yizhen Zheng, Alan Wee-Chung Liew, Fuyi Li, Shirui Pan

• [Paper]

• Online Fraud Detection via Test-Time Retrieval-Based Representation Enrichment (AAAI 2025)

• Yiran Qiao, Ningtao Wang, Yuncong Gao, Yang Yang, Xing Fu, Weiqiang Wang, Xiang Ao

• [Paper]

• Dynamic Neighborhood Modeling via Node-Subgraph Contrastive Learning for Graph-Based Fraud Detection (AAAI 2025)

• Zhizhi Yu, Chundong Liang, Xinglong Chang, Dongxiao He, Di Jin, Jianguo Wei

• [Paper]

• Unveiling the Threat of Fraud Gangs to Graph Neural Networks: Multi-Target Graph Injection Attacks Against GNN-Based Fraud Detectors (AAAI 2025)

• Jinhyeok Choi, Heehyeon Kim, Joyce Jiyoung Whang

• [Paper]

• ScamNet: Toward Explainable Large Language Model-Based Fraudulent Shopping Website Detection (AAAI 2025)

• Marzieh Bitaab, Alireza Karimi, Zhuoer Lyu, Ahmadreza Mosallanezhad, Adam Oest, Ruoyu Wang, Tiffany Bao, Yan Shoshitaishvili, Adam Doupé

• [Paper]

• Federated Gradient Boosting for Financial Fraud Detection: An Empirical Study in the Banking Sector (CIKM 2025)

• Dae-Young Park, In-Young Ko, Taek-Ho Lee, Junghye Lee

• [Paper]

• Neighbor-enhanced Graph Pre-training and Prompt Learning Framework for Fraud Detection (CIKM 2025)

• Ziyang Cheng, Jie Yang, Yixin Song, Dawei Cheng, Guang Yang, Bo Wang

• [Paper]

• Fraudulent Delivery Detection with Multimodal Courier Behavior Data in Last-Mile Delivery (CIKM 2025)

• Shanshan Wang, Sijing Duan, Shuxin Zhong, Zhiqing Hong, Zhiyuan Zhou, Hongyu Lin, Weijian Zuo, Desheng Zhang, Yi Ding

• [Paper]

• Fraud-Proof Revenue Division on Subscription Platforms (ICML 2025)

• Abheek Ghosh, Tzeh Yuan Neoh, Nicholas Teh, Giannis Tyrovolas

• [Paper]

• Mitigating Message Imbalance in Fraud Detection with Dual-View Graph Representation Learning (IJCAI 2025)

• Yudan Song, Yuecen Wei, Yuhang Lu, Qingyun Sun, Minglai Shao, Li-E Wang, Chunming Hu, Xianxian Li, Xingcheng Fu

• [Paper]

• Attention-based Conditional Random Field for Financial Fraud Detection (IJCAI 2025)

• Xiaoguang Wang, Chenxu Wang, Luyue Zhang, Xiaole Wang, Mengqin Wang, Huanlong Liu, Tao Qin

• [Paper]

• MutationGuard: A Graph and Temporal-Spatial Neural Method for Detecting Mutation Telecommunication Fraud (IJCAI 2025)

• Haitao Bai, Pinghui Wang, Ruofei Zhang, Ziyang Zhou, Juxiang Zeng, Yulou Su, Li Xing, Zhou Su, Chen Zhang, Lizhen Cui, Jun Hao, Wei Wang

• [Paper]

• Welcome to the Dark Side: Analyzing the Revenue Flows of Fraud in the Online Ad Ecosystem (WWW 2025)

• Emmanouil Papadogiannakis, Nicolas Kourtellis, Panagiotis Papadopoulos, Evangelos P. Markatos

• [Paper]

• Grad: Guided Relation Diffusion Generation for Graph Augmentation in Graph Fraud Detection (WWW 2025)

• Jie Yang, Rui Zhang, Ziyang Cheng, Dawei Cheng, Guang Yang, Bo Wang
• [Paper]

2024

• Revisiting Graph-Based Fraud Detection in Sight of Heterophily and Spectrum (AAAI 2024)
• Fan Xu, Nan Wang, Hao Wu, Xuezhi Wen, Xibin Zhao, Hai Wan

• [Paper]

• DiG-In-GNN: Discriminative Feature Guided GNN-Based Fraud Detector against Inconsistencies in Multi-Relation Fraud Graph (AAAI 2024)

• Jinghui Zhang, Zhengjia Xu, Dingyang Lv, Zhan Shi, Dian Shen, Jiahui Jin, Fang Dong
• [Paper]

• [Code]

• DGA-GNN: Dynamic Grouping Aggregation GNN for Fraud Detection (AAAI 2024)

• Mingjiang Duan, Tongya Zheng, Yang Gao, Gang Wang, Zunlei Feng, Xinyu Wang

• [Paper]

• Barely Supervised Learning for Graph-Based Fraud Detection (AAAI 2024)

• Hang Yu, Zhengyang Liu, Xiangfeng Luo

• [Paper]

• Pre-trained Online Contrastive Learning for Insurance Fraud Detection (AAAI 2024)

• Rui Zhang, Dawei Cheng, Jie Yang, Yi Ouyang, Xian Wu, Yefeng Zheng, Changjun Jiang

• [Paper]

• A Payment Transaction Pre-training Model for Fraud Transaction Detection (CIKM 2024)

• Wenxi Huang, Zhangyi Zhao, Xiaojun Chen, Qin Zhang, Mark Junjie Li, Hanjing Su, Qingyao Wu

• [Paper]

• Collaborative Fraud Detection on Large Scale Graph Using Secure Multi-Party Computation (CIKM 2024)

• Xin Liu, Xiaoyu Fan, Rong Ma, Kun Chen, Yi Li, Guosai Wang, Wei Xu

• [Paper]

• LEX-GNN: Label-Exploring Graph Neural Network for Accurate Fraud Detection (CIKM 2024)

• Woochang Hyun, Insoo Lee, Bongwon Suh
• [Paper]

• [Code]

• Graph-theoretical Approach to Enhance Accuracy of Financial Fraud Detection Using Synthetic Tabular Data Generation (CIKM 2024)

• Dae-Young Park

• [Paper]

• TROPICAL: Transformer-Based Hypergraph Learning for Camouflaged Fraudster Detection (ICDM 2024)

• Venus Haghighi, Behnaz Soltani, Nasrin Shabani, Jia Wu, Yang Zhang, Lina Yao, Quan Z. Sheng, Jian Yang

• [Paper]

• Partitioning Message Passing for Graph Fraud Detection (ICLR 2024)

• Wei Zhuo, Zemin Liu, Bryan Hooi, Bingsheng He, Guang Tan, Rizal Fathony, Jia Chen

• [Paper]

• Fraud Risk Mitigation in Real-Time Payments: A Strategic Agent-Based Analysis (IJCAI 2024)

• Katherine Mayo, Nicholas Grabill, Michael P. Wellman

• [Paper]

• SACNN: Self Attention-based Convolutional Neural Network for Fraudulent Behaviour Detection in Sports (IJCAI 2024)

• Maxx Richard Rahman, Lotfy H. Abdel Khaliq, Thomas Piper, Hans Geyer, Tristan Equey, Norbert Baume, Reid Aikin, Wolfgang Maass

• [Paper]

• Safeguarding Fraud Detection from Attacks: A Robust Graph Learning Approach (IJCAI 2024)

• Jiasheng Wu, Xin Liu, Dawei Cheng, Yi Ouyang, Xian Wu, Yefeng Zheng

• [Paper]

• Effective High-order Graph Representation Learning for Credit Card Fraud Detection (IJCAI 2024)

• Yao Zou, Dawei Cheng

• [Paper]

• Cost-Efficient Fraud Risk Optimization with Submodularity in Insurance Claim (KDD 2024)

• Yupeng Wu, Zhibo Zhu, Chaoyi Ma, Hong Qian, Xingyu Lu, Yangwenhui Zhang, Xiaobo Qin, Binjie Fei, Jun Zhou, Aimin Zhou

• [Paper]

• SEFraud: Graph-based Self-Explainable Fraud Detection via Interpretative Mask Learning (KDD 2024)

• Kaidi Li, Tianmeng Yang, Min Zhou, Jiahao Meng, Shendi Wang, Yihui Wu, Boshuai Tan, Hu Song, Lujia Pan, Fan Yu, Zhenli Sheng, Yunhai Tong

• [Paper]

• On Finding Bi-objective Pareto-optimal Fraud Prevention Rule Sets for Fintech Applications (KDD 2024)

• Chengyao Wen, Yin Lou

• [Paper]

• VecAug: Unveiling Camouflaged Frauds with Cohort Augmentation for Enhanced Detection (KDD 2024)

• Fei Xiao, Shaofeng Cai, Gang Chen, H. V. Jagadish, Beng Chin Ooi, Meihui Zhang

• [Paper]

• Friend or Foe? Mining Suspicious Behavior via Graph Capsule Infomax Detector against Fraudsters (WWW 2024)

• Xiangping Zheng, Bo Wu, Xun Liang, Wei Li

• [Paper]

• ZipZap: Efficient Training of Language Models for Large-Scale Fraud Detection on Blockchain (WWW 2024)

• Sihao Hu, Tiansheng Huang, Ka-Ho Chow, Wenqi Wei, Yanzhao Wu, Ling Liu
• [Paper]

2023

• Anti-Money Laundering by Group-Aware Deep Graph Learning (TKDE 2023)
• Dawei Cheng, Yujia Ye, Sheng Xiang, Zhenwei Ma, Ying Zhang, Changjun Jiang

• [Paper]

• Semi-supervised Credit Card Fraud Detection via Attribute-driven Graph Representation (AAAI 2023)

• Sheng Xiang, Mingzhi Zhu, Dawei Cheng, Enxia Li, Ruihui Zhao, Yi Ouyang, Ling Chen, Yefeng Zheng
• [Paper]

• [Code]

• A Framework for Detecting Frauds from Extremely Few Labels (WSDM 2023)

• Ya-Lin Zhang, Yi-Xuan Sun, Fangfang Fan, Meng Li, Yeyu Zhao, Wei Wang, Longfei Li, Jun Zhou, Jinghua Feng

• [Paper]

• Label Information Enhanced Fraud Detection against Low Homophily in Graphs (WWW 2023)

• Yuchen Wang, Jinghui Zhang, Zhengjie Huang, Weibin Li, Shikun Feng, Ziheng Ma, Yu Sun, Dianhai Yu, Fang Dong, Jiahui Jin, Beilun Wang, Junzhou Luo (WWW 2023)

• [Paper]

• BERT4ETH: A Pre-trained Transformer for Ethereum Fraud Detection (WWW 2023)

• Sihao Hu, Zhen Zhang, Bingqiao Luo, Shengliang Lu, Bingsheng He, Ling Liu
• [Paper]

2022

• The Importance of Future Information in Credit Card Fraud Detection (AISTATS 2022)
• Van Bach Nguyen, Kanishka Ghosh Dastidar, Michael Granitzer, Wissam Siblini

• [Paper]

• BRIGHT - Graph Neural Networks in Real-time Fraud Detection (CIKM 2022)

• Mingxuan Lu, Zhichao Han, Susie Xi Rao, Zitao Zhang, Yang Zhao, Yinan Shan, Ramesh Raghunathan, Ce Zhang, Jiawei Jiang

• [Paper]

• Dual-Augment Graph Neural Network for Fraud Detection (CIKM 2022)

• Qiutong Li, Yanshen He, Cong Xu, Feng Wu, Jianliang Gao, Zhao Li

• [Paper]

• Explainable Graph-based Fraud Detection via Neural Meta-graph Search (CIKM 2022)

• Zidi Qin, Yang Liu, Qing He, Xiang Ao

• [Paper]

• MetaRule: A Meta-path Guided Ensemble Rule Set Learning for Explainable Fraud Detection (CIKM 2022)

• Lu Yu, Meng Li, Xiaoguang Huang, Wei Zhu, Yanming Fang, Jun Zhou, Longfei Li

• [Paper]

• **User Behavior Pre-training for Online Fraud Det