/awesome-fraud-detection-papers

A curated list of data mining papers about fraud detection.

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Awesome Fraud Detection Research Papers.

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

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

2020

  • 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]

2019

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

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

  • 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]

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

  • 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]

  • 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]

  • 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]

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

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

2018

  • 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]

  • 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]

2017

  • 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]

  • 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]

2016

  • 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]

  • 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]

2015

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

  • 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)

  • 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]

  • 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]

2014

  • 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)

2013

  • 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)

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

    • Leman Akoglu, Christos Faloutsos
    • [Paper]

2012

  • 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]

2011

  • 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)

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

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

2010

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

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

    • Levente Kocsis, Andras George
    • [Paper]

2009

  • 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]

2007

  • 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)

  • 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]

2006

  • 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]

2005

  • 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)

  • 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]

2003

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

2000

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

1999

  • Statistical Challenges to Inductive Inference in Linked Data. (AISTATS 1999)

1998

  • 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]

1997

  • 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)

  • 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]

1995

  • 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]