Literature on Fraud Detection
Various Articles
Papers and Magazines
Workshops and Conferences
Bibliography
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[AFR97]
Emin Aleskerov, Bernd Freisleben, Bharat Rao. CARDWATCH: A Neural Network Based Database Mining System for Credit Card Fraud Detection. In: Proceedings of Computa- tional Intelligence for Financial Engineering (CIFEr), S. 220--226, 1997.
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[AME98]
Dean W. Abbott, I. Philip Matkovsky und John F. Elder.
An Evaluation of High-End Data Mining Tools for Fraud Detection.
In: Proceedings of the 1998 IEEE International Conference on Systems, Man, and Cybernetics, vol. 3, pp. 2836-2841, 1998.
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[ATW97]
Suhaya Abu-Hakima, Mansour Toloo, Tony White. A Multi-Agent Systems Approach for Fraud Detection in Personal Communication Systems. In: [Faw97], 1997.
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[Axe99]
Stefan Axelsson.
The Base-Rate Fallacy and its Implications for the Difficulty of Intrusion Detection.
In: Proceedings of the 6th ACM Conference on Computer and Communications Security, pp. 1-7, 1999.
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[BH]
Richard J. Bolton, David J. Hand
Statistical Fraud Detection: A Review.
Statistical Science, 17(3), 235-255.
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[BLH99a]
R. Brause, T. Langsdorf, M. Hepp.
Credit Card Fraud Detection by Adaptive Neural Data Mining.
Internal Report 7/99, FB Informatik, University of Frankfurt a.M., 1999
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[BLH99b]
R. Brause, T. Langsdorf, M. Hepp.
Neural Data Mining for Credit Card Fraud Detection.
In: Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence. pp. 103--106. 1999.
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[BS97a]
Peter Burge, John Shawe-Taylor. Detecting Cellular Fraud Using Adaptive Prototypes. In: [Faw97].
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[BS97b]
Peter Burge, John Shawe-Taylor. Fraud-Management Tools: First Prototype. ASPeCT -- Project, Januar 1997. See [ASPeCT].
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[BSCMPS97]
P. Burge, J. Shawe-Taylor, C. Cooke, Y. Moreau, B. Preneel, C. Stoermann.
Fraud Detection and Management in Mobile Telecommunications Networks.
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[CCLPS00]
Michael Cahill, Fei Chen, Diane Lambert, José Pinheiro, Don X. Sun.
Detecting Fraud in the Real World. In:
Handbook of Massive Datasets.
Kluewer. 2002.
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[CFPS99]
Philip K. Chan, Wei Fan, Andreas L. Prodromidis, Salvatore J. Stolfo. Distributed Data Mining in Credit Card Fraud Detection. In: IEEE Intelligent Systems, Bd. 14, Nr. 6, S. 67--74, 1999.
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[CLPS99]
Fei Chen, Diane Lambert, José Pinheiro, Don Sun.
Reducing Transaction Databases, Without Lagging Behind the Data or Losing Information.
Unpublished, 1999.
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[DB98]
Steven K. Donoho, Scott W. Bennett.
Fraud Detection and Discovery.
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[DC98]
J. R. Dorronsoro, C. Santa Cruz. Discrimination of overlapping data and credit card fraud detection. Technischer Bericht, Department of Computer Engineering, Universidad de Madrid, 1998.
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[DGSC97]
Jose R. Dorronsoro, Francisco Ginel, Carmen Sanchez, Carlos Santa Cruz.
Neural Fraud Detection in Credit Card Operations.
In: IEEE Transactions on Neural Networks, Nr. 4, Bd. 8, Juli 1997.
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[EN96]
Kazuo J. Ezawa, Steven W. Norton.
Constructing Bayesian Networks to Predict Uncollectible Telecommunications Accounts.
IEEE Expert, Nr. 5, Bd. 11, S. 45--51, 1996.
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[Faw97]
Tom Fawcett.
AI Approaches to Fraud Detection & Risk Management --- Papers from the 1997 AAAI Workshop,
Technical Report WS-97-07, Juli 1997, AAAI-Press.
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[FP97a]
Tom Fawcett and Foster Provost.
Adaptive Fraud Detection.
Data Mining and Knowledge Discovery, vol. 1, no. 3, p. {291-316}. 1997.
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[FP97b]
Tom Fawcett, Foster Provost.
Combining Data Mining and Machine Learning for Effective Fraud Detection. In: [Faw97].
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[Gos97]
Phil Gosset. Fraud Detection Concepts: Final Report. ASPeCT -- Project, November 1997. See [ASPeCT].
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[GH99]
Phil Gossett, Mark Hyland. Classification, Detection and Prosecution of Fraud on Mobile Networks. Proceedings of ACTS Mobile Summit, Sorrento, Italy, Juni 1999.
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[GR94]
Sushmito Ghosh, Douglas L. Reilly. Credit Card Fraud Detection with a Neural-Network. In: Proceedings of the 27th Hawaii International Conference on Information Systems, S. 621-- 630, 1994.
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[HDA98]
Mark Hyland, Jos Dumortier, Diana Alonso Blas. Legal Aspects of Fraud Detection. ASPeCT-Project.
See [ASPeCT].
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[Jen97]
David Jensen.
Prospective Assessment of AI Technologies for Fraud Detection: A Case Study.
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[KKN99]
Daniel A. Keim, Eleftherios E. Koutsofios, Stephen C. North. Visual Exploration of Large Telecommunication Data Sets. In: User Interfaces to Data Intensive Systems, S. 12-- 20, 1999.
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[MP96]
Yves Moreau, Bart Preneel. Definition of Fraud Detection Concepts. ASPeCT -- Project, August 1996. See [ASPeCT].
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[OTA95]
U. S. Congress, Office of Technology Assessment. Information
Technologies for Control of Money Laundering. U. S. Government
Printing Office, OTA-ITC-630, Washington DC, September 1995.
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[PF97]
Foster Provost, Tom Fawcett. Analysis and Visualization of Classifier
Performance: Comparison under Imprecise Class and Cost
Distributions. In: Proceedings of the Third International Conference
on Knowledge Discovery and Data Mining (KDD-97), 1997.
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[PF01]
Foster Provost, Tom Fawcett.
Robust Classification for Imprecise Environments. In: Machine
Learning, vol. 42, no. 3, pp. 203-231, 2001.
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[PFK98]
Foster Provost, Tom Fawcett, Ron Kohavi.
The Case Against Accuracy Estimation for Comparing Induction Algorithms.
Proceedings of the Fifteenth International Conference on Machine Learning (ICML-98), July 1998.
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[Sal97]
Steven Salzberg.
On Comparing Classifiers: Pitfalls to Avoid and a Recommended Approach.
In: Data Mining and Knowledge Discovery, Nr. 3, S. 317--328, 1997.
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[SFLPC97]
Salvatore J. Stolfo, David W. Fan, Wenke Lee, Andreas L. Prodromidis, Philip K. Chan. Credit Card Fraud Detection Using Meta-Learning: Issues and Initial Results. In: [Faw97].
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[Stö97]
Christof Störmann. Fraud Management Tool: Evaluation Report. ASPeCT -
Project, Oktober 1997. See [ASPeCT].
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