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Courses in winter term 2007/2008 / Master Seminar on Fraud Detection
Abstract
Topics

List of Topics:

  1. -- Introduction --
  2. Fraud Detection in Recommender Systems
    1. Bamshad Mobasher, Robin Burke, Runa Bhaumik, J.J. Sandvig (2007): Attacks and Remedies in Collabortive Recommendation IEEE Intelligent Systems May/June 2007, pp. 56-63.

      2. Optional Article:
    2. [ee] Bamshad Mobasher, Robin Burke, Runa Bhaumik, Chad Williams (2007): Towards Trustworthy Recommender Systems: An Analysis of Attack Models and Algorithm Robustness ACM Transactions on Internet Technology, Vol. 7, No. 2, May 2007.
  3. Fraud Detection with Bayesian and Neural Networks
    1. [ee] Sam Maes, Karl Tuyls, Bram Vanschoenwinkel, Bernard Manderick (2002): Credit Card Fraud Detection Using Bayesian and Neural Networks First International NAISO Congress on Neuro Fuzzy Technologies, Havana, Cuba.
  4. Fraud Detection based on Data Signature
    1. [ee] Corinna Cortes, Daryl Pregibon (2001): Signature-Based Methods for Data Streams Data Mining and Knowledge Discovery, Vol. 5, No. 3, Juli 2001, Pages 167-182.
  5. Fraud Detection in Sequential Data
    1. [ee] Terran Lane, Carla E. Brodley (1999): Temporal Sequence Learning and Data Reduction for Anomaly Detection ACM Transactions on Information and System Security, Vol. 2, No. 3, August 1999, Pages 295-331.

      2. Optional Article:
    2. [ee] Thomas G. Dietterich (2002): Machine Learning for Sequential Data: A Review Structural, Syntatic, and Statistic Pattern Recognition, Springer Berlin / Heidelberg, ISBN 978-3-540-44011-6.
  6. Case Based Sytems for Fraud Detection
    1. [ee] Richard Wheeles, Stuard Aitken (2000): Multiple Algorithms for Fraud Detection Knowledge-Based Systems, Elsevier.
  7. Relational Classification for Fraud Detection
    1. [ee] Jennifer Neville, Özgür Simsek, David Jensen, John Komoroske, Kelly Palmer, Henry Goldberg (2005): Using Relational Knowledge Discovery to Prevent Securities Fraud Proceeding of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining, Pages 449 - 458, ISBN 1-59593-135-X .

      2. AND
    2. [ee] Jennifer Neville, David Jensen, Lisa Friedland, Michael Hay (2003): Learning Relational Probability Trees Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, Pages 625 - 630, ISBN 1-58113-737-0.
  8. Boosting Naive Bayes for Fraud Detection
    1. [ee] Stijn Viaene, Richard A. Derrig, Guido Dedene (2004): A Case Study of Applying Boosting Naive Bayes to Claim Fraud Diagnosis IEEE Transactions on Knowledge and Data Engineering, Vol. 16, No. 5, May 2004.
  9. Improvement of Internal Control Systems
    1. [ee] Mieke Jans, Nadine Lybaert, Koen Vanhoof (2007): Data Mining for Fraud Detection: Toward an Improvement on Internal Control Systems? 30th Annual Congress European Accounting Association (EAA2007).
  10. Regression for Prediction of Bankruptcy
    1. [ee] Dean P. Foster, Robert A. Stine (2004): Variable Selection in Data Mining: Building a Predictive Model for Bankruptcy Journal of the American Statistical Association.
  11. Hybrid System (Decesion Trees and SVM)
    1. [ee] Sandhya Peddabachigari, Ajith Abraham, Crina Grosan, Johnson Thomas (2007): Modelling intrusion detection system using hybrid intelligent systems Journal of Network and Computer Applications, Volume 30, Issue 1, January 2007, Pages 114-132.