Fraud detection system: A survey
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[1] MingJian Tang,et al. Unsupervised Fraud Detection in Medicare Australia , 2011, AusDM.
[2] Panos Alexopoulos,et al. Towards a Generic Fraud Ontology in e-Government , 2007, ICE-B.
[3] Qi Liu,et al. Healthcare fraud detection : A survey and a clustering model incorporating Geolocation information , 2013 .
[4] Neha Sethi,et al. A Revived Survey of Various Credit Card Fraud Detection Techniques , 2014 .
[5] Yong Hu,et al. The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature , 2011, Decis. Support Syst..
[6] Chang-Tien Lu,et al. Survey of fraud detection techniques , 2004, IEEE International Conference on Networking, Sensing and Control, 2004.
[7] Gabriel Maciá-Fernández,et al. Fraud in roaming scenarios: an overview , 2009, IEEE Wireless Communications.
[8] Zhi-Hua Zhou,et al. Exploratory Undersampling for Class-Imbalance Learning , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[9] Rasim Muzaffer Musal. Two models to investigate Medicare fraud within unsupervised databases , 2010, Expert Syst. Appl..
[10] Wang Da-zhen,et al. Fraud Detection in Mobile Communication Networks , 2004 .
[11] David J. Hand,et al. Overcoming selectivity bias in evaluating new fraud detection systems for revolving credit operations , 2012 .
[12] Seungjin Choi,et al. Supervised Learning , 2009, Encyclopedia of Biometrics.
[13] Adam Wierzbicki,et al. Using Stereotypes to Identify Risky Transactions in Internet Auctions , 2010, 2010 IEEE Second International Conference on Social Computing.
[14] R. Patidar,et al. Credit Card Fraud Detection Using Neural Network , 2011 .
[15] Maria L. Gini,et al. Design and implementation of a secure multi-agent marketplace , 2004, Electron. Commer. Res. Appl..
[16] Vinicius Almendra,et al. Finding the needle: A risk-based ranking of product listings at online auction sites for non-delivery fraud prediction , 2013, Expert Syst. Appl..
[17] Erik Kaestner,et al. License To Steal: How Fraud bleeds America's Health Care System , 2000 .
[18] Rekha Bhowmik. Data Mining Techniques in Fraud Detection , 2008, J. Digit. Forensics Secur. Law.
[19] Jaeho Jang,et al. A Comparison of Neural Network, Statistical Methods, and Variable Choice for Life Insurers' Financial Distress Prediction , 2006 .
[20] Janez Bester,et al. Bidirectional Artificial Neural Networks for Mobile-Phone Fraud Detection , 2009 .
[21] Rekha Bhowmik,et al. Detecting Auto Insurance Fraud by Data Mining Techniques , 2011 .
[22] Matthew Self,et al. Bayesian Classification , 1988, AAAI.
[23] Pradeep Ray,et al. Artificial immune systems for the detection of credit card fraud: an architecture, prototype and preliminary results , 2012, Inf. Syst. J..
[24] Fugee Tsung,et al. Applying manufacturing batch techniques to fraud detection with incomplete customer information , 2007 .
[25] John W. Fraas,et al. A Statistical Process Control Approach , 2012 .
[26] John Shawe-Taylor,et al. Report highlights: Detection of fraud in mobile telecommunications , 1999 .
[27] Georges Dionne,et al. Optimal Auditing with Scoring: Theory and Application to Insurance Fraud , 2009, Manag. Sci..
[28] El-Bachir Belhadji,et al. Development of an Expert System for the Automatic Detection of Automobile Insurance Fraud , 1998 .
[29] Michaela M. Black,et al. Classification of Customer Call Data in the Presence of Concept Drift and Noise , 2002, Soft-Ware.
[30] Ekrem Duman,et al. Detecting credit card fraud by decision trees and support vector machines , 2011 .
[31] Ekrem Duman,et al. A cost-sensitive decision tree approach for fraud detection , 2013, Expert Syst. Appl..
[32] Wei Fan,et al. Systematic data selection to mine concept-drifting data streams , 2004, KDD.
[33] Mahmoud Reza Hashemi,et al. An adaptive profile based fraud detection framework for handling concept drift , 2013, 2013 10th International ISC Conference on Information Security and Cryptology (ISCISC).
[34] Duen Horng Chau,et al. Fraud Detection in Electronic Auction , 2005 .
[35] Melih Kirlidog,et al. A Fraud Detection Approach with Data Mining in Health Insurance , 2012 .
[36] Kate Smith-Miles,et al. Resilient Identity Crime Detection , 2012, IEEE Transactions on Knowledge and Data Engineering.
[37] John Shawe-Taylor,et al. Novel Techniques for Fraud Detection in Mobile Telecommunication Networks , 2007 .
[38] Anthony Brabazon,et al. Identifying online credit card fraud using Artificial Immune Systems , 2010, IEEE Congress on Evolutionary Computation.
[39] Rüdiger W. Brause,et al. Neural data mining for credit card fraud detection , 1999, Proceedings 11th International Conference on Tools with Artificial Intelligence.
[40] Nitesh V. Chawla,et al. SMOTE: Synthetic Minority Over-sampling Technique , 2002, J. Artif. Intell. Res..
[41] 尹麗莎. Fraud Detection for Internet Auctions: A Data Mining Approach , 2008 .
[42] Rong-Chang Chen,et al. Personalized Approach Based on SVM and ANN for Detecting Credit Card Fraud , 2005, 2005 International Conference on Neural Networks and Brain.
[43] Constantinos S. Hilas,et al. Designing an expert system for fraud detection in private telecommunications networks , 2009, Expert Syst. Appl..
[44] Adem Karahoca,et al. Fraud Detection Using an Adaptive Neuro-Fuzzy Inference System in Mobile Telecommunication Networks , 2009, J. Multiple Valued Log. Soft Comput..
[45] Longbing Cao,et al. Effective detection of sophisticated online banking fraud on extremely imbalanced data , 2012, World Wide Web.
[46] Navneet Vidyarthi,et al. A Fuzzy-Based Algorithm for Auditors to Detect Element of Fraud in Settled Insurance Claims , 2003 .
[47] Martijn Onderwater,et al. Detecting unusual user proles with outlier detection techniques , 2010 .
[48] Sachin J. Pukale,et al. A REVIEW OF ANOMALY BASED INTRUSIONS DETECTION IN MULTI-TIER WEB APPLICATIONS , 2012 .
[49] Zahid Halim,et al. Fraudulent call detection for mobile networks , 2010, 2010 International Conference on Information and Emerging Technologies.
[50] Mohammad Abdollahi Azgomi,et al. A Taxonomy of Frauds and Fraud Detection Techniques , 2009, ICISTM.
[51] Pankaj Richhariya,et al. A Survey on Financial Fraud Detection Methodologies , 2012 .
[52] Cesar Analide,et al. Telecommunications Fraud: Problem Analysis-an Agent-based KDD Perspective , 2009 .
[53] Christian W. Omlin,et al. Credit Card Transactions, Fraud Detection, and Machine Learning: Modelling Time with LSTM Recurrent Neural Networks , 2009, Innovations in Neural Information Paradigms and Applications.
[54] Gianluca Bontempi,et al. Learned lessons in credit card fraud detection from a practitioner perspective , 2014, Expert Syst. Appl..
[55] Jian Ma,et al. Fraud detection in telecommunication: A rough fuzzy set based approach , 2008, 2008 International Conference on Machine Learning and Cybernetics.
[56] Ekrem Duman,et al. Detecting credit card fraud by genetic algorithm and scatter search , 2011, Expert Syst. Appl..
[57] Saěso Dězeroski. Relational Data Mining , 2001, Encyclopedia of Machine Learning and Data Mining.
[58] Luigi Barone,et al. Nature-Inspired Techniques in the Context of Fraud Detection , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[59] Rudolf Kruse,et al. Fuzzy neural network , 2008, Scholarpedia.
[60] D. Hand,et al. Unsupervised Profiling Methods for Fraud Detection , 2002 .
[61] V. Subramaniyaswamy,et al. Data mining approach for subscription-fraud detection in telecommunication sector , 2014 .
[62] John A. Major,et al. EFD: A Hybrid Knowledge/Statistical-Based System for the Detection of Fraud , 2002 .
[63] Shunzhi Zhu,et al. Health care fraud detection using nonnegative matrix factorization , 2011, 2011 6th International Conference on Computer Science & Education (ICCSE).
[64] Joos Vandewalle,et al. Detection of Mobile Phone Fraud Using Supervised Neural Networks: A First Prototype , 1997, ICANN.
[65] Jos van Hillegersberg,et al. Electronic Fraud Detection in the U.S. Medicaid Healthcare Program: Lessons Learned from other Industries , 2011, AMCIS.
[66] Wayne Petherick,et al. An Exploration of Automobile Insurance Fraud , 2003 .
[67] Tatsuya Minegishi,et al. Proposal of Credit Card Fraudulent Use Detection by Online-type Decision Tree Construction and Verification of Generality , 2013 .
[68] Yin Shan,et al. Mining Medical Specialist Billing Patterns for Health Service Management , 2008, AusDM.
[69] Patrick L. Brockett,et al. Assessing Consumer Fraud Risk in Insurance Claims , 2009 .
[70] Liang Lei,et al. Card Fraud Detection by Inductive Learning and Evolutionary Algorithm , 2012, 2012 Sixth International Conference on Genetic and Evolutionary Computing.
[71] Marco Vieira,et al. Supporting Fraud Analysis in Mobile Telecommunications Using Case-Based Reasoning , 2008, ECCBR.
[72] Georgios C. Anagnostopoulos,et al. Knowledge-Based Intelligent Information and Engineering Systems , 2003, Lecture Notes in Computer Science.
[73] Azzedine Boukerche,et al. Behavior-Based Intrusion Detection in Mobile Phone Systems , 2002, J. Parallel Distributed Comput..
[74] Wen-Shenq Juang,et al. An electronic online bidding auction protocol with both security and efficiency , 2006, Appl. Math. Comput..
[75] Christos Faloutsos,et al. Detecting Fraudulent Personalities in Networks of Online Auctioneers , 2006, PKDD.
[76] V Jyothsna,et al. A Review of Anomaly based Intrusion Detection Systems , 2011 .
[77] Mercedes Ayuso,et al. A Bayesian dichotomous model with asymmetric link for fraud in insurance , 2008 .
[78] Byungtae Lee,et al. Empirical analysis of online auction fraud: Credit card phantom transactions , 2010, Expert Syst. Appl..
[79] Paul Resnick,et al. Reputation systems , 2000, CACM.
[80] Constantinos S. Hilas,et al. Testing the Fraud Detection Ability of Different User Profiles by Means of FF-NN Classifiers , 2006, ICANN.
[81] Martin Hepp,et al. Credit Card Fraud Detection by Adaptive Neural Data Mining , 1999 .
[82] Tom Chen,et al. Design and implementation , 2006, IEEE Commun. Mag..
[83] Dibyen Majumdar,et al. Price comparison: A reliable approach to identifying shill bidding in online auctions? , 2012, Electron. Commer. Res. Appl..
[84] Dimitris K. Tasoulis,et al. Exponentially weighted moving average charts for detecting concept drift , 2012, Pattern Recognit. Lett..
[85] Wen-Hsi Chang,et al. An effective early fraud detection method for online auctions , 2012, Electron. Commer. Res. Appl..
[86] Orlando Belo,et al. Applying User Signatures on Fraud Detection in Telecommunications Networks , 2011, ICDM.
[87] Wen-Hsi Chang,et al. An early fraud detection mechanism for online auctions based on phased modeling , 2009, 2009 Joint Conferences on Pervasive Computing (JCPC).
[88] Liu Zhixin,et al. 2012 International Conference on Information Management, Innovation Management and Industrial Engineering Insurance Fraud Identification Research Based on Fuzzy Support Vector Machine with Dual Membership , 2022 .
[89] Xiaojin Zhu,et al. Introduction to Semi-Supervised Learning , 2009, Synthesis Lectures on Artificial Intelligence and Machine Learning.
[90] Dominik Olszewski,et al. A probabilistic approach to fraud detection in telecommunications , 2012, Knowl. Based Syst..
[91] Montserrat Guillen,et al. Selection Bias and Auditing Policies for Insurance Claims , 2007 .
[92] Guido Dedene,et al. Auto claim fraud detection using Bayesian learning neural networks , 2005, Expert Syst. Appl..
[93] Simon Padgett,et al. About the Association of Certified Fraud Examiners and the Report to the Nations on Occupational Fraud and Abuse , 2015 .
[94] John Langford,et al. Cost-sensitive learning by cost-proportionate example weighting , 2003, Third IEEE International Conference on Data Mining.
[95] Jionghua Jin,et al. A survey on statistical methods for health care fraud detection , 2008, Health care management science.
[96] José R. Dorronsoro,et al. Neural fraud detection in credit card operations , 1997, IEEE Trans. Neural Networks.
[97] Patrick L. Brockett,et al. Fraud Classification Using Principal Component Analysis of Ridits , 2002 .
[98] M Sasirekha,et al. A Defense Mechanism for Credit Card Fraud Detection , 2012 .
[99] A. Roli. Artificial Neural Networks , 2012, Lecture Notes in Computer Science.
[100] Komal Mule,et al. Credit Card Fraud Detection Using Hidden Markov Model (HMM) , 2014 .
[101] Chih-Hung Wu,et al. A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy , 2007, Expert Syst. Appl..
[102] Lawrence W. Lan,et al. DISCRETE CHOICE MODELING FOR BUNDLED AUTOMOBILE INSURANCE POLICIES , 2005 .
[103] San-Yih Hwang,et al. A process-mining framework for the detection of healthcare fraud and abuse , 2006, Expert Syst. Appl..
[104] Ashish Sureka,et al. Mining eBay: Bidding Strategies and Shill Detection , 2002, WEBKDD.
[105] Mohammad Kazem Akbari,et al. A novel model for credit card fraud detection using Artificial Immune Systems , 2014, Appl. Soft Comput..
[106] TERRAN LANE,et al. Temporal sequence learning and data reduction for anomaly detection , 1999, TSEC.
[107] Jian Pei,et al. Data Mining Trends and Research Frontiers , 2012 .
[108] Chaochang Chiu,et al. Internet Auction Fraud Detection Using Social Network Analysis and Classification Tree Approaches , 2011, Int. J. Electron. Commer..
[109] Wan-Shiou Yang,et al. A Process Pattern Mining Framework for the Detection of Health Care Fraud and Abuse , 2003 .
[110] Michael M. Wagner,et al. Healthcare System , 2021, Encyclopedia of Gerontology and Population Aging.
[111] Vladimir Zaslavsky,et al. Credit Card Fraud Detection Using Self-Organizing Maps , 2006 .
[112] Mercedes Ayuso,et al. Detection of Automobile Insurance Fraud with Discrete Choice Models and Misclassified Claims , 2002 .
[113] Georges Dionne,et al. Replacement Cost Endorsement and Opportunistic Fraud in Automobile Insurance , 2000 .
[114] Kian-Lee Tan,et al. PumaMart: a parallel and autonomous agents based internet marketplace , 2004, Electron. Commer. Res. Appl..
[115] M. S. Hitam,et al. A Review on a Classification Framework for Supporting Decision Making in Crime Prevention , 2015 .
[116] Hong Zhao,et al. Applying data mining to detect fraud behavior in customs declaration , 2002, Proceedings. International Conference on Machine Learning and Cybernetics.
[117] P. Brockett,et al. Using Kohonen's Self-Organizing Feature Map to Uncover Automobile Bodily Injury Claims Fraud , 1998 .
[118] Andrew B. Whinston,et al. Building Trust in Online Auction Markets Through an Economic Incentive Mechanism , 2003, Decis. Support Syst..
[119] Mohd Rizam Abu Bakar,et al. Fraud detection in telecommunication industry using Gaussian mixed model , 2013, 2013 International Conference on Research and Innovation in Information Systems (ICRIIS).
[120] César Rego,et al. A classification of online bidders in a private value auction: evidence from eBay , 2007 .
[121] Marko Bajec,et al. An expert system for detecting automobile insurance fraud using social network analysis , 2011, Expert Syst. Appl..
[122] RobeRt Kelley,et al. WHERE CAN $700 BILLION IN WASTE BE CUT ANNUALLY FROM THE U.S. HEALTHCARE SYSTEM? , 2009 .
[123] Niall M. Adams,et al. Transaction aggregation as a strategy for credit card fraud detection , 2009, Data Mining and Knowledge Discovery.
[124] Shamik Sural,et al. Two-Stage Credit Card Fraud Detection Using Sequence Alignment , 2006, ICISS.
[125] Wen-Hsi Chang,et al. Analysis of fraudulent behavior strategies in online auctions for detecting latent fraudsters , 2014, Electron. Commer. Res. Appl..
[126] Francisco Herrera,et al. Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics , 2012, Expert Syst. Appl..
[127] Kee Siong Ng,et al. Detecting Non-compliant Consumers in Spatio-Temporal Health Data: A Case Study from Medicare Australia , 2010, 2010 IEEE International Conference on Data Mining Workshops.
[128] Wei Xu,et al. Random Rough Subspace Based Neural Network Ensemble for Insurance Fraud Detection , 2011, 2011 Fourth International Joint Conference on Computational Sciences and Optimization.
[129] S. Benson Edwin Raj,et al. Analysis on credit card fraud detection methods , 2011 .
[130] Constantinos S. Hilas,et al. An Application of Decision Trees for Rule Extraction Towards Telecommunications Fraud Detection , 2007, KES.
[131] H. Lookman Sithic,et al. Survey of Insurance Fraud Detection Using Data Mining Techniques , 2013, ArXiv.
[132] I. Sumaiya Thaseen,et al. An Integrated Intrusion Detection System for Credit Card Fraud Detection , 2012, ACITY.
[133] Francisca Nonyelum Ogwueleka. DATA MINING APPLICATION IN CREDIT CARD FRAUD DETECTION SYSTEM , 2011 .
[134] Chao Lan,et al. Anomaly Detection , 2018, Encyclopedia of GIS.
[135] Wojtek Kowalczyk,et al. Finding Fraud in Health Insurance Data with Two-Layer Outlier Detection Approach , 2011, DaWaK.
[136] Shiguo Wang,et al. A Comprehensive Survey of Data Mining-Based Accounting-Fraud Detection Research , 2010, 2010 International Conference on Intelligent Computation Technology and Automation.
[137] Krishna Kumar Tripathi,et al. Survey on Credit Card Fraud Detection Methods , 2012 .
[138] Nada Lavrač,et al. Relational Data Mining , 2018, Encyclopedia of Social Network Analysis and Mining. 2nd Ed..
[139] Carsten A. W. Paasch. Credit card fraud detection using artificial neural networks tuned by genetic algorithms , 2008 .
[140] Gillian Dobbie,et al. Evaluating Fraud Detection Algorithms Using an Auction Data Generator , 2012, 2012 IEEE 12th International Conference on Data Mining Workshops.
[141] M. Bajec,et al. Method for selection of motor insurance fraud management system components based on business performance , 2011 .
[142] Charles Francis,et al. Using support vector machines to detect medical fraud and abuse , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[143] Shi-Jen Lin,et al. Combining ranking concept and social network analysis to detect collusive groups in online auctions , 2012, Expert Syst. Appl..
[144] Iren Valova,et al. A Real-Time Self-Adaptive Classifier for Identifying Suspicious Bidders in Online Auctions , 2013, Comput. J..
[145] Vinicius Almendra,et al. A Supervised Learning Process to Elicit Fraud Cases in Online Auction Sites , 2011, 2011 13th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing.
[146] Asherry Magalla. Prevention and Detection of Cyber Crimes in Tanzania as Described by Cyber Crime Act, No. 13 of 2015 , 2018 .
[147] Abhinav Srivastava,et al. Credit Card Fraud Detection Using Hidden Markov Model , 2008, IEEE Transactions on Dependable and Secure Computing.
[148] Rafael Maranzato,et al. Fraud detection in reputation systems in e-markets using logistic regression and stepwise optimization , 2010, SIAP.
[149] Stephen P. D’Arcy,et al. Predictive Modeling in Automobile Insurance : A Preliminary Analysis , 2005 .
[150] S. O. Falaki,et al. Probabilistic Credit Card Fraud Detection System in Online Transactions , 2012 .
[151] L. Weiss. License to Steal: How Fraud Bleeds America's Health Care System , 2001 .
[152] Felix Naumann,et al. Data fusion , 2009, CSUR.
[153] Graham J. Williams,et al. On-Line Unsupervised Outlier Detection Using Finite Mixtures with Discounting Learning Algorithms , 2000, KDD '00.
[154] Hendrawan,et al. A research on usage pattern and analysis technique for communication fraud: SIM cloning and surfing , 2006, 2006 International Conference on Computing & Informatics.
[155] João Gama,et al. A survey on concept drift adaptation , 2014, ACM Comput. Surv..
[156] Mirjana Pejic-Bach. Invited Paper: Profiling Intelligent Systems Applications in Fraud Detection and Prevention: Survey of Research Articles , 2010, 2010 International Conference on Intelligent Systems, Modelling and Simulation.
[157] Fletcher Lu,et al. Detecting Fraud in Health Insurance Data: Learning to Model Incomplete Benford's Law Distributions , 2005, ECML.
[158] Mohammad Mehdi Sepehri,et al. A data mining framework for detecting subscription fraud in telecommunication , 2011, Eng. Appl. Artif. Intell..
[159] Salvatore J. Stolfo,et al. Credit Card Fraud Detection Using Meta-Learning: Issues and Initial Results 1 , 1997 .
[160] John Akhilomen. Data Mining Application for Cyber Credit-Card Fraud Detection System , 2013, ICDM.
[161] Mrinal Mugdh,et al. A Decision Support Tool for Identifying Abuse of Controlled Substances by ForwardHealth Medicaid Members , 2010, Journal of hospital marketing & public relations.
[162] P. Bentley,et al. Fuzzy Darwinian Detection of Credit Card Fraud , 2000 .
[163] H. Abbass,et al. Online Adaptation in Learning Classifier Systems : Stream Data Mining , 2004 .
[164] Olivier Festor,et al. A survey on fraud and service misuse in voice over IP (VoIP) networks , 2011, Inf. Secur. Tech. Rep..
[165] Azzedine Boukerche,et al. An artificial immune based intrusion detection model for computer and telecommunication systems , 2004, Parallel Comput..
[166] Chaochang Chiu,et al. A Proposed Data Mining Approach for Internet Auction Fraud Detection , 2007, PAISI.
[167] David J. Hand,et al. Statistical fraud detection: A review , 2002 .
[168] Phil Gosset,et al. Classification, Detection and Prosecution of Fraud on Mobile Networks , 1999 .
[169] Hussein A. Abdou,et al. Credit card fraud and detection techniques : a review , 2009 .
[170] Carla E. Brodley,et al. Temporal sequence learning and data reduction for anomaly detection , 1998, CCS '98.
[171] VARUN CHANDOLA,et al. Anomaly detection: A survey , 2009, CSUR.
[172] Peter Brennan,et al. A comprehensive survey of methods for overcoming the class imbalance problem in fraud detection , 2012 .
[173] Wei Jiang,et al. A statistical process control approach to business activity monitoring , 2007 .
[174] Song Chen,et al. A Novel Approach to Uncover Health Care Frauds through Spectral Analysis , 2013, 2013 IEEE International Conference on Healthcare Informatics.
[175] Yizhak Idan,et al. Discovery of fraud rules for telecommunications—challenges and solutions , 1999, KDD '99.
[176] Indre Zliobaite,et al. Learning under Concept Drift: an Overview , 2010, ArXiv.
[177] Petra Perner,et al. Data Mining - Concepts and Techniques , 2002, Künstliche Intell..
[178] Miguel Pironet San-Bento Almeida,et al. Classification for Fraud Detection with Social Network Analysis , 2009 .
[179] Nidal F. Shilbayeh,et al. Cloning SIM Cards Usability Reduction in Mobile Networks , 2013, Journal of Network and Systems Management.
[180] Alair Pereira do Lago,et al. Credit Card Fraud Detection with Artificial Immune System , 2008, ICARIS.
[181] Hyun-Chul Kim,et al. Constructing support vector machine ensemble , 2003, Pattern Recognit..
[182] Gillian Dobbie,et al. Detecting online auction shilling frauds using supervised learning , 2014, Expert Syst. Appl..
[183] Makoto Yokoo,et al. The effect of false-name bids in combinatorial auctions: new fraud in internet auctions , 2004, Games Econ. Behav..
[184] Tom Fawcett,et al. Adaptive Fraud Detection , 1997, Data Mining and Knowledge Discovery.
[185] Rolf Oppliger,et al. Internet security: firewalls and beyond , 1997, CACM.
[186] Volker Tresp,et al. Call-Based Fraud Detection in Mobile Communication Networks Using a Hierarchical Regime-Switching Model , 1998, NIPS.
[187] Kate Smith-Miles,et al. A Comprehensive Survey of Data Mining-based Fraud Detection Research , 2010, ArXiv.
[188] Guido Dedene,et al. Strategies for detecting fraudulent claims in the automobile insurance industry , 2007, Eur. J. Oper. Res..
[189] Qibei Lu,et al. Research on Credit Card Fraud Detection Model Based on Class Weighted Support Vector Machine , 2011 .
[190] A. Muthukumaravel,et al. Credit Card Fraud Detection Using Hidden Markov Model-A Survey , 2014 .
[191] Jos van Hillegersberg,et al. Predicting Healthcare Fraud in Medicaid: A Multidimensional Data Model and Analysis Techniques for Fraud Detection , 2013 .
[192] Rong-Chang Chen,et al. Detecting Credit Card Fraud by Using Questionnaire-Responded Transaction Model Based on Support Vector Machines , 2004, IDEAL.
[193] Shamik Sural,et al. BLAST-SSAHA Hybridization for Credit Card Fraud Detection , 2009, IEEE Transactions on Dependable and Secure Computing.
[194] Mohd Shafri Kamaruddin,et al. Leveraging Missing Values in Call Detail Record Using Naïve Bayes for Fraud Analysis , 2008, 2008 International Conference on Information Networking.
[195] John A. Major,et al. EFD: A hybrid knowledge/statistical‐based system for the detection of fraud , 1992, Int. J. Intell. Syst..
[196] Wang Dong,et al. A feature extraction method for fraud detection in mobile communication networks , 2004, Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788).
[197] Devesh Narayan,et al. A Survey on Hidden Markov Model for Credit Card Fraud Detection , 2012 .
[198] K. Crocker,et al. Insurance Fraud and Optimal Claims Settlement Strategies* , 2002, The Journal of Law and Economics.
[199] Haiping Xu,et al. A Multi-State Bayesian Network for Shill Verification in Online Auctions , 2010, SEKE.
[200] Peter Kulchyski. and , 2015 .
[201] Michael Massoth,et al. Telephony Fraud Detection in Next Generation Networks , 2012, ICT 2012.
[202] Amparo Alonso-Betanzos,et al. Filter Methods for Feature Selection - A Comparative Study , 2007, IDEAL.
[203] J. Christopher Westland,et al. Employing transaction aggregation strategy to detect credit card fraud , 2012, Expert Syst. Appl..
[204] Yao-Hsu Tsai,et al. Using CommonKADS Method to Build Prototype System in Medical Insurance Fraud Detection , 2014, J. Networks.
[205] Douglas L. Reilly,et al. Credit card fraud detection with a neural-network , 1994, 1994 Proceedings of the Twenty-Seventh Hawaii International Conference on System Sciences.
[206] Roy McNamara,et al. Report highlights: Networks - where does the real threat lie? , 1999 .
[207] Gadi Pinkas,et al. Unsupervised Profiling for Identifying Superimposed Fraud , 1999, PKDD.
[208] Tung-Shou Chen,et al. A new binary support vector system for increasing detection rate of credit card fraud , 2006, Int. J. Pattern Recognit. Artif. Intell..
[209] Claudio A. Perez,et al. Subscription fraud prevention in telecommunications using fuzzy rules and neural networks , 2006, Expert Syst. Appl..
[210] Min-Jung Kim,et al. A Neural Classifier with Fraud Density Map for Effective Credit Card Fraud Detection , 2002, IDEAL.
[211] John Shawe-Taylor,et al. Detection of fraud in mobile telecommunications , 1999, Inf. Secur. Tech. Rep..
[212] Azlinah Mohamed,et al. Telecommunication Fraud Prediction Using Backpropagation Neural Network , 2009, 2009 International Conference of Soft Computing and Pattern Recognition.
[213] Gianluca Bontempi,et al. Racing for Unbalanced Methods Selection , 2013, IDEAL.
[214] M. Krivko,et al. A hybrid model for plastic card fraud detection systems , 2010, Expert Syst. Appl..
[215] Wen-Hsi Chang,et al. A Multiple-Phased Modeling Method to Identify Potential Fraudsters in Online Auctions , 2010, 2010 Second International Conference on Computer Research and Development.
[216] Pedro A. Ortega,et al. A Medical Claim Fraud/Abuse Detection System based on Data Mining: A Case Study in Chile , 2006, DMIN.
[217] Bhawna Mallick,et al. A review of Fraud Detection Techniques: Credit Card , 2012 .
[218] Bharat K. Bhargava,et al. Cheating in online auction - Towards explaining the popularity of English auction , 2007, Electron. Commer. Res. Appl..
[219] NIMISHA PHILIP,et al. CREDIT CARD FRAUD DETECTION BASED ON BEHAVIOR MINING , 2012 .
[220] Krzysztof Ostaszewski,et al. Fuzzy Techniques of Pattern Recognition in Risk and Claim Classification , 1995 .
[221] H. Dominic Covvey,et al. Adaptive Fraud Detection Using Benford's Law , 2006, Canadian Conference on AI.
[222] Justin Zhan,et al. Towards Fraud Detection Methodologies , 2010, 2010 5th International Conference on Future Information Technology.
[223] Wen-Hsi Chang,et al. A novel two-stage phased modeling framework for early fraud detection in online auctions , 2011, Expert Syst. Appl..
[224] H. Koh,et al. Data mining applications in healthcare. , 2005, Journal of healthcare information management : JHIM.
[225] Haiping Xu,et al. Combating online in-auction fraud: Clues, techniques and challenges , 2009, Comput. Sci. Rev..
[226] Olatz Arbelaitz,et al. Consolidated Tree Classifier Learning in a Car Insurance Fraud Detection Domain with Class Imbalance , 2005, ICAPR.
[227] Cindy Durtschi,et al. The effective use of Benford's Law to assist in detecting fraud in accounting data , 2004 .
[228] Ronald J. Brachman,et al. Brief Application Description; Visual Data Mining: Recognizing Telephone Calling Fraud , 2004, Data Mining and Knowledge Discovery.
[229] Herbert I. Weisberg,et al. QUANTITATIVE METHODS FOR DETECTING FRAUDULENT AUTOMOBILE BODILY INJURY CLAIMS , 1998 .
[230] Philip S. Yu,et al. Mining concept-drifting data streams using ensemble classifiers , 2003, KDD '03.
[231] Paris A. Mastorocostas,et al. An application of supervised and unsupervised learning approaches to telecommunications fraud detection , 2008, Knowl. Based Syst..
[232] Masoumeh Zareapoor,et al. Analysis of Credit Card Fraud Detection Techniques: based on Certain Design Criteria , 2012 .
[233] Masoumeh Zareapoor,et al. FraudMiner: A Novel Credit Card Fraud Detection Model Based on Frequent Itemset Mining , 2014, TheScientificWorldJournal.
[234] Haiping Xu,et al. Real-Time Model Checking for Shill Detection in Live Online Auctions , 2009, Software Engineering Research and Practice.
[235] Jon T. S. Quah,et al. Real Time Credit Card Fraud Detection using Computational Intelligence , 2007, 2007 International Joint Conference on Neural Networks.
[236] Sol M. Shatz,et al. Automated inference of shilling behavior in online auction systems , 2012 .
[237] A. Annie Portia,et al. Analysis on credit card fraud detection methods , 2011, 2011 International Conference on Computer, Communication and Electrical Technology (ICCCET).
[238] M Syeda,et al. Parallel granular neural networks for fast credit card fraud detection , 2002, 2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291).
[239] Victor C. M. Leung,et al. Enhancing security using mobility-based anomaly detection in cellular mobile networks , 2006, IEEE Trans. Veh. Technol..
[240] A. Aleem,et al. Internet auction fraud: The evolving nature of online auctions criminality and the mitigating framework to address the threat , 2011 .
[241] Johan H van Heerden,et al. Detecting fraud in cellular telephone networks , 2005 .
[242] Volker Tresp,et al. Fraud detection in communication networks using neural and probabilistic methods , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).
[243] Sharon Tennyson,et al. Claims Auditing in Automobile Insurance , 2001 .
[244] Tao Guo,et al. Neural data mining for credit card fraud detection , 2008, 2008 International Conference on Machine Learning and Cybernetics.
[245] John Shawe-Taylor,et al. Fraud detection and management in mobile telecommunications networks , 1997 .
[246] Ekrem Duman,et al. A Novel and Successful Credit Card Fraud Detection System Implemented in a Turkish Bank , 2013, 2013 IEEE 13th International Conference on Data Mining Workshops.
[247] Paul Resnick,et al. Reputation Systems: Facilitating Trust in Internet Interactions , 2000 .
[248] Ronnie Alves,et al. Detecting telecommunications fraud based on signature clustering analysis , 2007 .
[249] Stuart J. Russell,et al. Online bagging and boosting , 2005, 2005 IEEE International Conference on Systems, Man and Cybernetics.
[250] Guido Dedene,et al. A case study of applying boosting naive Bayes to claim fraud diagnosis , 2004, IEEE Transactions on Knowledge and Data Engineering.
[251] Paul Krause,et al. Neural Network Rule Extraction to Detect Credit Card Fraud , 2011, EANN/AIAI.
[252] Hongxing He,et al. Application of neural networks to detection of medical fraud , 1997 .
[253] Cecil Eng Huang Chua,et al. Fighting Internet auction fraud: an assessment and proposal , 2004, Computer.
[254] Ernestina Menasalvas Ruiz,et al. Learning recurring concepts from data streams with a context-aware ensemble , 2011, SAC.
[255] Sharon Tennyson,et al. Claims Auditing in Automobile Insurance: Fraud Detection and Deterrence Objectives , 2002 .
[256] Robert C. Wolpert,et al. A Review of the , 1985 .
[257] William L. Fithen,et al. State of the Practice of Intrusion Detection Technologies , 2000 .
[258] Alok Gupta,et al. User heterogeneity and its impact on electronic auction market design: an empirical exploration , 2004 .
[259] R Nedunchezhian,et al. BOAT adaptive credit card fraud detection system , 2010, 2010 IEEE International Conference on Computational Intelligence and Computing Research.
[260] Siddhartha Bhattacharyya,et al. Data mining for credit card fraud: A comparative study , 2011, Decis. Support Syst..