• 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.

• 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]

• 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 Detection (KDD 2022)

  • Can Liu, Yuncong Gao, Li Sun, Jinghua Feng, Hao Yang, Xiang Ao
  • [Paper]

• Accelerated GNN Training with DGL and RAPIDS cuGraph in a Fraud Detection Workflow (KDD 2022)

  • Brad Rees, Xiaoyun Wang, Joe Eaton, Onur Yilmaz, Rick Ratzel, Dominque LaSalle
  • [Paper]

• A View into YouTube View Fraud (WWW 2022)

  • Dhruv Kuchhal, Frank Li
  • [Paper]

• Beyond Bot Detection: Combating Fraudulent Online Survey Takers (WWW 2022)

  • Ziyi Zhang, Shuofei Zhu, Jaron Mink, Aiping Xiong, Linhai Song, Gang Wang
  • [Paper]

• AUC-oriented Graph Neural Network for Fraud Detection (WWW 2022)

  • Mengda Huang, Yang Liu, Xiang Ao, Kuan Li, Jianfeng Chi, Jinghua Feng, Hao Yang, Qing He
  • [Paper]

• H2-FDetector: A GNN-based Fraud Detector with Homophilic and Heterophilic Connections (WWW 2022)

  • Fengzhao Shi, Yanan Cao, Yanmin Shang, Yuchen Zhou, Chuan Zhou, Jia Wu
  • [Paper]

• Active Learning for Human-in-the-loop Customs Inspection (TKDE 2022)

  • Sundong Kim, Tung-Duong Mai, Thi Nguyen Duc Khanh, Sungwon Han, Sungwon Park, Karandeep Singh, Meeyoung Cha
  • [Paper]
  • [Code]

• Knowledge Sharing via Domain Adaptation in Customs Fraud Detection (AAAI 2022)

  • Sungwon Park, Sundong Kim, Meeyoung Cha
  • [Paper]

• Towards Consumer Loan Fraud Detection: Graph Neural Networks with Role-Constrained Conditional Random Field (AAAI 2021)

  • Bingbing Xu, Huawei Shen, Bing-Jie Sun, Rong An, Qi Cao, Xueqi Cheng
  • [Paper]

• Modeling the Field Value Variations and Field Interactions Simultaneously for Fraud Detection (AAAI 2021)

  • Dongbo Xi, Bowen Song, Fuzhen Zhuang, Yongchun Zhu, Shuai Chen, Tianyi Zhang, Yuan Qi, Qing He
  • [Paper]

• IFDDS: An Anti-fraud Outbound Robot (AAAI 2021)

  • Zihao Wang, Minghui Yang, Chunxiang Jin, Jia Liu, Zujie Wen, Saishuai Liu, Zhe Zhang
  • [Paper]

• Modeling Heterogeneous Graph Network on Fraud Detection: A Community-based Framework with Attention Mechanism (CIKM 2021)

  • Li Wang, Peipei Li, Kai Xiong, Jiashu Zhao, Rui Lin
  • [Paper]

• Fraud Detection under Multi-Sourced Extremely Noisy Annotations (CIKM 2021)

  • Chuang Zhang, Qizhou Wang, Tengfei Liu, Xun Lu, Jin Hong, Bo Han, Chen Gong
  • [Paper]

• Adversarial Reprogramming of Pretrained Neural Networks for Fraud Detection (CIKM 2021)

  • Lingwei Chen, Yujie Fan, Yanfang Ye
  • [Paper]

• Fine-Grained Element Identification in Complaint Text of Internet Fraud (CIKM 2021)

  • Tong Liu, Siyuan Wang, Jingchao Fu, Lei Chen, Zhongyu Wei, Yaqi Liu, Heng Ye, Liaosa Xu, Weiqiang Wang, Xuanjing Huang
  • [Paper]

• Could You Describe the Reason for the Transfer: A Reinforcement Learning Based Voice-Enabled Bot Protecting Customers from Financial Frauds (CIKM 2021)

  • Zihao Wang, Fudong Wang, Haipeng Zhang, Minghui Yang, Shaosheng Cao, Zujie Wen, Zhe Zhang
  • [Paper]

• Online Credit Payment Fraud Detection via Structure-Aware Hierarchical Recurrent Neural Network (IJCAI 2021)

  • Wangli Lin, Li Sun, Qiwei Zhong, Can Liu, Jinghua Feng, Xiang Ao, Hao Yang
  • [Paper]

• Intention-aware Heterogeneous Graph Attention Networks for Fraud Transactions Detection (KDD 2021)

  • Can Liu, Li Sun, Xiang Ao, Jinghua Feng, Qing He, Hao Yang
  • [Paper]

• Live-Streaming Fraud Detection: A Heterogeneous Graph Neural Network Approach (KDD 2021)

  • Haishuai Wang, Zhao Li, Peng Zhang, Jiaming Huang, Pengrui Hui, Jian Liao, Ji Zhang, Jiajun Bu
  • [Paper]

• Customs Fraud Detection in the Presence of Concept Drift (IncrLearn@ICDM 2021)

  • Tung-Duong Mai, Kien Hoang, Aitolkyn Baigutanova, Gaukhartas Alina, Sundong Kim
  • [Paper]

• Pick and Choose: A GNN-based Imbalanced Learning Approach for Fraud Detection (WWW 2021)

  • Yang Liu, Xiang Ao, Zidi Qin, Jianfeng Chi, Jinghua Feng, Hao Yang, Qing He
  • [Paper]

• Spatio-Temporal Attention-Based Neural Network for Credit Card Fraud Detection (AAAI 2020)

  • Dawei Cheng, Sheng Xiang, Chencheng Shang, Yiyi Zhang, Fangzhou Yang, Liqing Zhang
  • [Paper]

• FlowScope: Spotting Money Laundering Based on Graphs (AAAI 2020)

  • Xiangfeng Li, Shenghua Liu, Zifeng Li, Xiaotian Han, Chuan Shi, Bryan Hooi, He Huang, Xueqi Cheng
  • [Paper]
  • [Code]

• Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters (CIKM 2020)

  • Yingtong Dou, Zhiwei Liu, Li Sun, Yutong Deng, Hao Peng, Philip S. Yu
  • [Paper]
  • [Code]

• Loan Default Analysis with Multiplex Graph Learning (CIKM 2020)

  • Binbin Hu, Zhiqiang Zhang, Jun Zhou, Jingli Fang, Quanhui Jia, Yanming Fang, Quan Yu, Yuan Qi
  • [Paper]

• Error-Bounded Graph Anomaly Loss for GNNs (CIKM 2020)

  • Tong Zhao, Chuchen Deng, Kaifeng Yu, Tianwen Jiang, Daheng Wang, Meng Jiang
  • [Paper]
  • [Code]

• BotSpot: A Hybrid Learning Framework to Uncover Bot Install Fraud in Mobile Advertising (CIKM 2020)

  • Tianjun Yao, Qing Li, Shangsong Liang, Yadong Zhu
  • [Paper]
  • [Code]

• Early Fraud Detection with Augmented Graph Learning (DLG@KDD 2020)

  • Tong Zhao, Bo Ni, Wenhao Yu, Meng Jiang
  • [Paper]

• NAG: Neural Feature Aggregation Framework for Credit Card Fraud Detection (ICDM 2020)

  • Kanishka Ghosh Dastidar, Johannes Jurgovsky, Wissam Siblini, Liyun He-Guelton, Michael Granitzer
  • [Paper]

• Heterogeneous Mini-Graph Neural Network and Its Application to Fraud Invitation Detection (ICDM 2020)

  • Yong-Nan Zhu, Xiaotian Luo, Yu-Feng Li, Bin Bu, Kaibo Zhou, Wenbin Zhang, Mingfan Lu
  • [Paper]

• Collaboration Based Multi-Label Propagation for Fraud Detection (IJCAI 2020)

  • Haobo Wang, Zhao Li, Jiaming Huang, Pengrui Hui, Weiwei Liu, Tianlei Hu, Gang Chen
  • [Paper]

• The Behavioral Sign of Account Theft: Realizing Online Payment Fraud Alert (IJCAI 2020)

  • Cheng Wang
  • [Paper]

• Federated Meta-Learning for Fraudulent Credit Card Detection (IJCAI 2020)

  • Wenbo Zheng, Lan Yan, Chao Gou, Fei-Yue Wang
  • [Paper]

• Robust Spammer Detection by Nash Reinforcement Learning (KDD 2020)

  • Yingtong Dou, Guixiang Ma, Philip S. Yu, Sihong Xie
  • [Paper]
  • [Code]

• DATE: Dual Attentive Tree-aware Embedding for Customs Fraud Detection (KDD 2020)

  • Sundong Kim, Yu-Che Tsai, Karandeep Singh, Yeonsoo Choi, Etim Ibok, Cheng-Te Li, Meeyoung Cha
  • [Paper]
  • [Code]

• Fraud Transactions Detection via Behavior Tree with Local Intention Calibration (KDD 2020)

  • Can Liu, Qiwei Zhong, Xiang Ao, Li Sun, Wangli Lin, Jinghua Feng, Qing He, Jiayu Tang
  • [Paper]

• Interleaved Sequence RNNs for Fraud Detection (KDD 2020)

  • Bernardo Branco, Pedro Abreu, Ana Sofia Gomes, Mariana S. C. Almeida, João Tiago Ascensão, Pedro Bizarro
  • [Paper]

• GCN-Based User Representation Learning for Unifying Robust Recommendation and Fraudster Detection (SIGIR 2020)

  • Shijie Zhang, Hongzhi Yin, Tong Chen, Quoc Viet Nguyen Hung, Zi Huang, Lizhen Cui
  • [Paper]

• Alleviating the Inconsistency Problem of Applying Graph Neural Network to Fraud Detection (SIGIR 2020)

  • Zhiwei Liu, Yingtong Dou, Philip S. Yu, Yutong Deng, Hao Peng
  • [Paper]
  • [Code]

• Friend or Faux: Graph-Based Early Detection of Fake Accounts on Social Networks (WWW 2020)

  • Adam Breuer, Roee Eilat, Udi Weinsberg
  • [Paper]

• Financial Defaulter Detection on Online Credit Payment via Multi-view Attributed Heterogeneous Information Network (WWW 2020)

  • Qiwei Zhong, Yang Liu, Xiang Ao, Binbin Hu, Jinghua Feng, Jiayu Tang, Qing He
  • [Paper]

• ASA: Adversary Situation Awareness via Heterogeneous Graph Convolutional Networks (WWW 2020)

  • Rui Wen, Jianyu Wang, Chunming Wu, Jian Xiong
  • [Paper]

• Modeling Users' Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection (WWW 2020)

  • Yongchun Zhu, Dongbo Xi, Bowen Song, Fuzhen Zhuang, Shuai Chen, Xi Gu, Qing He
  • [Paper]

• SliceNDice: Mining Suspicious Multi-attribute Entity Groups with Multi-view Graphs (DSAA 2019)

  • Hamed Nilforoshan, Neil Shah
  • [Paper]
  • [Code]

• FARE: Schema-Agnostic Anomaly Detection in Social Event Logs (DSAA 2019)

  • Neil Shah
  • [Paper]

• Cash-Out User Detection Based on Attributed Heterogeneous Information Network with a Hierarchical Attention Mechanism (AAAI 2019)

  • Binbin Hu, Zhiqiang Zhang, Chuan Shi, Jun Zhou, Xiaolong Li, Yuan Qi
  • [Paper]
  • [Code]

• GeniePath: Graph Neural Networks with Adaptive Receptive Paths (AAAI 2019)

  • Ziqi Liu, Chaochao Chen, Longfei Li, Jun Zhou, Xiaolong Li, Le Song, Yuan Qi
  • [Paper]
  • [Code]

• SAFE: A Neural Survival Analysis Model for Fraud Early Detection (AAAI 2019)

  • Panpan Zheng, Shuhan Yuan, Xintao Wu
  • [Paper]
  • [Code]

• One-Class Adversarial Nets for Fraud Detection (AAAI 2019)

  • Panpan Zheng, Shuhan Yuan, Xintao Wu, Jun Li, Aidong Lu
  • [Paper]
  • [Code]

• Uncovering Download Fraud Activities in Mobile App Markets (ASONAM 2019)

  • Yingtong Dou, Weijian Li, Zhirong Liu, Zhenhua Dong, Jiebo Luo, Philip S. Yu
  • [Paper]

• Spam Review Detection with Graph Convolutional Networks (CIKM 2019)

  • Ao Li, Zhou Qin, Runshi Liu, Yiqun Yang, Dong Li
  • [Paper]
  • [Code]

• Key Player Identification in Underground Forums Over Attributed Heterogeneous Information Network Embedding Framework (CIKM 2019)

  • Yiming Zhang, Yujie Fan, Yanfang Ye, Liang Zhao, Chuan Shi
  • [Paper]
  • [Code]

• CatchCore: Catching Hierarchical Dense Subtensor (ECML-PKDD 2019)

  • Wenjie Feng, Shenghua Liu, Huawei Shen, and Xueqi Cheng
  • [Paper]
  • [Code]

• Spotting Collective Behaviour of Online Frauds in Customer Reviews (IJCAI 2019)

  • Sarthika Dhawan, Siva Charan Reddy Gangireddy, Shiv Kumar, Tanmoy Chakraborty
  • [Paper]
  • [Code]

• A Semi-Supervised Graph Attentive Network for Fraud Detection (ICDM 2019)

  • Daixin Wang, Jianbin Lin, Peng Cui, Quanhui Jia, Zhen Wang, Yanming Fang, Quan Yu, Jun Zhou, Shuang Yang, and Qi Yuan
  • [Paper]
  • [Code]

• EigenPulse: Detecting Surges in Large Streaming Graphs with Row Augmentation (PAKDD 2019)

  • Jiabao Zhang, Shenghua Liu, Wenjian Yu, Wenjie Feng, Xueqi Cheng
  • [Paper]

• Uncovering Insurance Fraud Conspiracy with Network Learning (SIGIR 2019)

  • Chen Liang, Ziqi Liu, Bin Liu, Jun Zhou, Xiaolong Li, Shuang Yang, Yuan Qi
  • [Paper]

• A Contrast Metric for Fraud Detection in Rich Graphs (TKDE 2019)

  • Shenghua Liu, Bryan Hooi, Christos Faloutsos
  • [Paper]

• Think Outside the Dataset: Finding Fraudulent Reviews using Cross-Dataset Analysis (WWW 2019)

  • Shirin Nilizadeh, Hojjat Aghakhani, Eric Gustafson, Christopher Kruegel, Giovanni Vigna
  • [Paper]

• Securing the Deep Fraud Detector in Large-Scale E-Commerce Platform via Adversarial Machine Learning Approach (WWW 2019)

  • Qingyu Guo, Zhao Li, Bo An, Pengrui Hui, Jiaming Huang, Long Zhang, Mengchen Zhao
  • [Paper]

• No Place to Hide: Catching Fraudulent Entities in Tensors (WWW 2019)

  • Yikun Ban, Xin Liu, Ling Huang, Yitao Duan, Xue Liu, Wei Xu
  • [Paper]

• FdGars: Fraudster Detection via Graph Convolutional Networks in Online App Review System (WWW 2019)

  • Rui Wen, Jianyu Wang and Yu Huang
  • [Paper]
  • [Code]

• Heterogeneous Graph Neural Networks for Malicious Account Detection (CIKM 2018)

  • Ziqi Liu, Chaochao Chen, Xinxing Yang, Jun Zhou, Xiaolong Li, and Le Song
  • [Paper]
  • [Code]

• Reinforcement Mechanism Design for Fraudulent Behaviour in e-Commerce (AAAI 2018)

  • Qingpeng Cai, Aris Filos-Ratsikas, Pingzhong Tang, Yiwei Zhang
  • [Paper]

• Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees (AAAI 2018)

  • Dennis J. N. J. Soemers, Tim Brys, Kurt Driessens, Mark H. M. Winands, Ann Nowé
  • [Paper]

• Nextgen AML: Distributed Deep Learning Based Language Technologies to Augment Anti Money Laundering Investigation(ACL 2018)

  • Jingguang Han, Utsab Barman, Jeremiah Hayes, Jinhua Du, Edward Burgin, Dadong Wan
  • [Paper]

• Preserving Privacy of Fraud Detection Rule Sharing Using Intel's SGX (CIKM 2018)

  • Daniel Deutch, Yehonatan Ginzberg, Tova Milo
  • [Paper]

• Deep Structure Learning for Fraud Detection (ICDM 2018)

  • Haibo Wang, Chuan Zhou, Jia Wu, Weizhen Dang, Xingquan Zhu, Jilong Wang
  • [Paper]

• Learning Sequential Behavior Representations for Fraud Detection (ICDM 2018)

  • Jia Guo, Guannan Liu, Yuan Zuo, Junjie Wu
  • [Paper]

• Impression Allocation for Combating Fraud in E-commerce Via Deep Reinforcement Learning with Action Norm Penalty (IJCAI 2018)

  • Mengchen Zhao, Zhao Li, Bo An, Haifeng Lu, Yifan Yang, Chen Chu
  • [Paper]

• Tax Fraud Detection for Under-Reporting Declarations Using an Unsupervised Machine Learning Approach (KDD 2018)

  • Daniel de Roux, Boris Perez, Andrés Moreno, María-Del-Pilar Villamil, César Figueroa
  • [Paper]

• Collective Fraud Detection Capturing Inter-Transaction Dependency (KDD 2018)

  • Bokai Cao, Mia Mao, Siim Viidu, Philip Yu
  • [Paper]

• Fraud Detection with Density Estimation Trees (KDD 2018)

  • Fraud Detection with Density Estimation Trees
  • [Paper]

• Real-time Constrained Cycle Detection in Large Dynamic Graphs (VLDB 2018)

  • Xiafei Qiu, Wubin Cen, Zhengping Qian, You Peng, Ying Zhang, Xuemin Lin, Jingren Zhou
  • [Paper]

• REV2: Fraudulent User Prediction in Rating Platforms (WSDM 2018)

  • Srijan Kumar, Bryan Hooi, Disha Makhija, Mohit Kumar, Christos Faloutsos, V. S. Subrahmanian
  • [Paper]
  • [Code]

• Exposing Search and Advertisement Abuse Tactics and Infrastructure of Technical Support Scammers (WWW 2018)

  • Bharat Srinivasan, Athanasios Kountouras, Najmeh Miramirkhani, Monjur Alam, Nick Nikiforakis, Manos Antonakakis, Mustaque Ahamad
  • [Paper]

• ZooBP: Belief Propagation for Heterogeneous Networks (VLDB 2017)

  • Dhivya Eswaran, Stephan Gunnemann, Christos Faloutsos, Disha Makhija, Mohit Kumar
  • [Paper]
  • [Code]

• Behavioral Analysis of Review Fraud: Linking Malicious Crowdsourcing to Amazon and Beyond (AAAI 2017)

  • Parisa Kaghazgaran, James Caverlee, Majid Alfifi
  • [Paper]

• Detection of Money Laundering Groups: Supervised Learning on Small Networks (AAAI 2017)

  • David Savage, Qingmai Wang, Xiuzhen Zhang, Pauline Chou, Xinghuo Yu
  • [Paper]

• Spectrum-based Deep Neural Networks for Fraud Detection (CIKM 2017)

  • Shuhan Yuan, Xintao Wu, Jun Li, Aidong Lu
  • [Paper]

• HoloScope: Topology-and-Spike Aware Fraud Detection (CIKM 2017)

  • Shenghua Liu, Bryan Hooi, Christos Faloutsos
  • [Paper]

• The Many Faces of Link Fraud (ICDM 2017)

  • Neil Shah, Hemank Lamba, Alex Beutel, Christos Faloutsos
  • [Paper]

• HitFraud: A Broad Learning Approach for Collective Fraud Detection in Heterogeneous Information Networks (ICDM 2017)

  • Bokai Cao, Mia Mao, Siim Viidu, Philip S. Yu
  • [Paper]

• GANG: Detecting Fraudulent Users in Online Social Networks via Guilt-by-Association on Directed Graphs (ICDM 2017)

  • Binghui Wang, Neil Zhenqiang Gong, Hao Fu
  • [Paper]
  • [Code]

• Improving Card Fraud Detection Through Suspicious Pattern Discovery (IEA/AIE 2017)

  • Fabian Braun, Olivier Caelen, Evgueni N. Smirnov, Steven Kelk, Bertrand Lebichot:
  • [Paper]

• Online Reputation Fraud Campaign Detection in User Ratings (IJCAI 2017)

  • Chang Xu, Jie Zhang, Zhu Sun
  • [Paper]

• Uncovering Unknown Unknowns in Financial Services Big Data by Unsupervised Methodologies: Present and Future trends (KDD 2017)

  • Gil Shabat, David Segev, Amir Averbuch
  • [Paper]

• PD-FDS: Purchase Density based Online Credit Card Fraud Detection System (KDD 2017)

  • Youngjoon Ki, Ji Won Yoon
  • [Paper]

• HiDDen: Hierarchical Dense Subgraph Detection with Application to Financial Fraud Detection (SDM 2017)

  • Si Zhang, Dawei Zhou, Mehmet Yigit Yildirim, Scott Alcorn, Jingrui He, Hasan Davulcu, Hanghang Tong
  • [Paper]

• A Fraud Resilient Medical Insurance Claim System (AAAI 2016)

  • Yuliang Shi, Chenfei Sun, Qingzhong Li, Lizhen Cui, Han Yu, Chunyan Miao
  • [Paper]

• A Graph-Based, Semi-Supervised, Credit Card Fraud Detection System (COMPLEX NETWORKS 2016)

  • Bertrand Lebichot, Fabian Braun, Olivier Caelen, Marco Saerens
  • [Paper]

• FRAUDAR: Bounding Graph Fraud in the Face of Camouflage (KDD 2016)

  • Bryan Hooi, Hyun Ah Song, Alex Beutel, Neil Shah, Kijung Shin, Christos Faloutsos
  • [Paper]
  • [Code]

• Identifying Anomalies in Graph Streams Using Change Detection (KDD 2016)

  • William Eberle and Lawrence Holde
  • [Paper]

• FairPlay: Fraud and Malware Detection in Google Play (SDM 2016)

  • Mahmudur Rahman, Mizanur Rahman, Bogdan Carbunar, Duen Horng Chau
  • [Paper]

• BIRDNEST: Bayesian Inference for Ratings-Fraud Detection (SDM 2016)

  • Bryan Hooi, Neil Shah, Alex Beutel, Stephan Günnemann, Leman Akoglu, Mohit Kumar, Disha Makhija, Christos Faloutsos
  • [Paper]

• Understanding the Detection of View Fraud in Video Content Portals (WWW 2016)

  • Miriam Marciel, Rubén Cuevas, Albert Banchs, Roberto Gonzalez, Stefano Traverso, Mohamed Ahmed, Arturo Azcorra
  • [Paper]

• Toward An Intelligent Agent for Fraud Detection — The CFE Agent (AAAI 2015)

  • Joe Johnson
  • [Paper]

• Graph Analysis for Detecting Fraud, Waste, and Abuse in Healthcare Data (AAAI 2015)

  • Juan Liu, Eric Bier, Aaron Wilson, Tomonori Honda, Kumar Sricharan, Leilani Gilpin, John Alexis Guerra Gómez, Daniel Davies
  • [Paper]

• Robust System for Identifying Procurement Fraud (AAAI 2015)

  • Amit Dhurandhar, Rajesh Kumar Ravi, Bruce Graves, Gopikrishnan Maniachari, Markus Ettl
  • [Paper]

• Fraud Transaction Recognition: A Money Flow Network Approach (CIKM 2015)

  • Renxin Mao, Zhao Li, Jinhua Fu
  • [Paper]

• Towards Collusive Fraud Detection in Online Reviews (ICDM 2015)

  • Chang Xu, Jie Zhang
  • [Paper]

• Catch the Black Sheep: Unified Framework for Shilling Attack Detection Based on Fraudulent Action Propagation (IJCAI 2015)

  • Yongfeng Zhang, Yunzhi Tan, Min Zhang, Yiqun Liu, Tat-Seng Chua, Shaoping Ma
  • [Paper]

• Collective Opinion Spam Detection: Bridging Review Networks and Metadata (KDD 2015)

  • Shebuti Rayana, Leman Akoglu
  • [Paper]
  • [Code]

• Graph-Based User Behavior Modeling: From Prediction to Fraud Detection (KDD 2015)

  • Alex Beutel, Leman Akoglu, Christos Faloutsos
  • [Paper]

• FrauDetector: A Graph-Mining-based Framework for Fraudulent Phone Call Detection (KDD 2015)

  • Vincent S. Tseng, Jia-Ching Ying, Che-Wei Huang, Yimin Kao, Kuan-Ta Chen
  • [Paper]

• A Framework for Intrusion Detection Based on Frequent Subgraph Mining (SDM 2015)

  • Vitali Herrera-Semenets, Niusvel Acosta-Mendoza, Andres Gago-Alonso
  • [Paper]

• Crowd Fraud Detection in Internet Advertising (WWW 2015)

  • Tian Tian, Jun Zhu, Fen Xia, Xin Zhuang, Tong Zhang
  • [Paper]

• Spotting Suspicious Link Behavior with fBox: An Adversarial Perspective (ICDM 2014)

  • Neil Shah, Alex Beutel, Brian Gallagher, Christos Faloutsos
  • [Paper]
  • [Code]

• Fraudulent Support Telephone Number Identification Based on Co-Occurrence Information on the Web (AAAI 2014)

  • Xin Li, Yiqun Liu, Min Zhang, Shaoping Ma
  • [Paper]

• Corporate Residence Fraud Detection (KDD 2014)

  • Enric Junqué de Fortuny, Marija Stankova, Julie Moeyersoms, Bart Minnaert, Foster J. Provost, David Martens
  • [Paper]

• Graphical Models for Identifying Fraud and Waste in Healthcare Claims (SDM 2014)

  • Peder A. Olsen, Ramesh Natarajan, Sholom M. Weiss
  • [Paper]

• Improving Credit Card Fraud Detection with Calibrated Probabilities (SDM 2014)

  • Alejandro Correa Bahnsen, Aleksandar Stojanovic, Djamila Aouada, Björn E. Ottersten
  • [Paper]

• Large Graph Mining: Patterns, Cascades, Fraud Detection, and Algorithms (WWW 2014)

  • Christos Faloutsos
  • [Paper]

• Opinion Fraud Detection in Online Reviews by Network Effects (AAAI 2013)

  • Leman Akoglu, Rishi Chandy, Christos Faloutsos
  • [Paper]

• Using Social Network Knowledge for Detecting Spider Constructions in Social Security Fraud (ASONAM 2013)

  • Véronique Van Vlasselaer, Jan Meskens, Dries Van Dromme, Bart Baesens
  • [Paper]

• Ranking Fraud Detection for Mobile Apps: a Holistic View (CIKM 2013)

  • Hengshu Zhu, Hui Xiong, Yong Ge, Enhong Chen
  • [Paper]

• Using Co-Visitation Networks for Detecting Large Scale Online Display Advertising Exchange Fraud (KDD 2013)

  • Ori Stitelman, Claudia Perlich, Brian Dalessandro, Rod Hook, Troy Raeder, Foster J. Provost
  • [Paper]

• Adaptive Adversaries: Building Systems to Fight Fraud and Cyber Intruders (KDD 2013)

  • Ari Gesher
  • [Paper]

• Anomaly, Event, and Fraud Detection in Large Network Datasets (WSDM 2013)

  • Leman Akoglu, Christos Faloutsos
  • [Paper]

• Fraud Detection: Methods of Analysis for Hypergraph Data (ASONAM 2012)

  • Anna Leontjeva, Konstantin Tretyakov, Jaak Vilo, and Taavi Tamkivi
  • [Paper]

• Online Modeling of Proactive Moderation System for Auction Fraud Detection (WWW 2012)

  • Liang Zhang, Jie Yang, Belle L. Tseng
  • [Paper]

• A Machine-Learned Proactive Moderation System for Auction Fraud Detection (CIKM 2011)

  • Liang Zhang, Jie Yang, Wei Chu, Belle L. Tseng
  • [Paper]

• A Taxi Driving Fraud Detection System (ICDM 2011)

  • Yong Ge, Hui Xiong, Chuanren Liu, Zhi-Hua Zhou
  • [Paper]

• Utility-Based Fraud Detection (IJCAI 2011)

  • Luís Torgo, Elsa Lopes
  • [Paper]

• A Pattern Discovery Approach to Retail Fraud Detection (KDD 2011)

  • Prasad Gabbur, Sharath Pankanti, Quanfu Fan, Hoang Trinh
  • [Paper]

• Hunting for the Black Swan: Risk Mining from Text (ACL 2010)

  • JL Leidner, F Schilder
  • [Paper]

• Fraud Detection by Generating Positive Samples for Classification from Unlabeled Data (ACL 2010)

  • Levente Kocsis, Andras George
  • [Paper]

• SVM-based Credit Card Fraud Detection with Reject Cost and Class-Dependent Error Cost (PAKDD 2009)

  • En-hui Zheng,Chao Zou,Jian Sun, Le Chen
  • [Paper]

• An Approach for Automatic Fraud Detection in the Insurance Domain (AAAI 2009)

  • Alexander Widder, Rainer v. Ammon, Gerit Hagemann, Dirk Schönfeld
  • [Paper]

• Relational Data Pre-Processing Techniques for Improved Securities Fraud Detection (KDD 2007)

  • Andrew S. Fast, Lisa Friedland, Marc E. Maier, Brian J. Taylor, David D. Jensen, Henry G. Goldberg, John Komoroske
  • [Paper]

• Uncovering Fraud in Direct Marketing Data with a Fraud Auditing Case Builder (PKDD 2007)

  • Fletcher Lu
  • [Paper]

• Netprobe: A Fast and Scalable System for Fraud Detection in Online Auction Networks (WWW 2007)

  • Shashank Pandit, Duen Horng Chau, Samuel Wang, Christos Faloutsos
  • [Paper]

• Data Mining Approaches to Criminal Career Analysis (ICDM 2006)

  • Jeroen S. De Bruin, Tim K. Cocx, Walter A. Kosters, Jeroen F. J. Laros, Joost N. Kok
  • [Paper]

• Large Scale Detection of Irregularities in Accounting Data (ICDM 2006)

  • Stephen Bay, Krishna Kumaraswamy, Markus G. Anderle, Rohit Kumar, David M. Steier
  • [Paper]

• Camouflaged Fraud Detection in Domains with Complex Relationships (KDD 2006)

  • Sankar Virdhagriswaran, Gordon Dakin
  • [Paper]

• Detecting Fraudulent Personalities in Networks of Online Auctioneers (PKDD 2006)

  • Duen Horng Chau, Shashank Pandit, Christos Faloutsos
  • [Paper]

• Technologies to Defeat Fraudulent Schemes Related to Email Requests (AAAI 2005)

  • Edoardo Airoldi, Bradley Malin, and Latanya Sweeney
  • [Paper]

• AI Technologies to Defeat Identity Theft Vulnerabilities (AAAI 2005)

  • Latanya Sweeney
  • [Paper]

• Detecting Fraud in Health Insurance Data: Learning to Model Incomplete Benford's Law Distributions (ECML 2005)

  • Fletcher Lu, J. Efrim Boritz
  • [Paper]

• Using Relational Knowledge Discovery to Prevent Securities Fraud (KDD 2005)

  • Jennifer Neville, Özgür Simsek, David D. Jensen, John Komoroske, Kelly Palmer, Henry G. Goldberg
  • [Paper]

• Applying Data Mining in Investigating Money Laundering Crimes (KDD 2003)
  • Zhongfei (Mark) Zhang, John J. Salerno, Philip S. Yu
  • [Paper]

• Document Classification and Visualisation to Support the Investigation of Suspected Fraud (PKDD 2000)
  • Johan Hagman, Domenico Perrotta, Ralf Steinberger, and Aristi de Varfis
  • [Paper]

• Statistical Challenges to Inductive Inference in Linked Data. (AISTATS 1999)
  • David Jensen
  • [Paper]

• Toward Scalable Learning with Non-Uniform Class and Cost Distributions: A Case Study in Credit Card Fraud Detection (KDD 1998)

  • Phillip K Chan, Salvatore J Stolfo
  • [Paper]

• Call-Based Fraud Detection in Mobile Communication Networks Using a Hierarchical Regime-Switching Model (NIPS 1998)

  • Jaakko Hollmén, Volker Tresp
  • [Paper]

• Detection of Mobile Phone Fraud Using Supervised Neural Networks: A First Prototype (ICANN 1997)

  • Yves Moreau, Herman Verrelst, Joos Vandewalle
  • [Paper]

• Prospective Assessment of AI Technologies for Fraud Detection: A Case Study (AAAI 1997)

  • David Jensen
  • [Paper]

• Credit Card Fraud Detection Using Meta-Learning: Issues and Initial Results (AAAI 1997)

  • Salvatore J. Stolfo, David W. Fan, Wenke Lee and Andreas L. Prodromidis
  • [Paper]

• Fraud: Uncollectible Debt Detection Using a Bayesian Network Based Learning System: A Rare Binary Outcome with Mixed Data Structures (UAI 1995)
  • Kazuo J. Ezawa, Til Schuermann
  • [Paper]

License

• CC0 Universal