Adaptive Fraud Detection

@article{citeulike:788096, abstract = {. One method for detecting fraud is to check for suspicious changes in user behavior. This paper describes the automatic design of user profiling methods for the purpose of fraud detection, using a series of data mining techniques. Specifically, we use a rule-learning program to uncover indicators of fraudulent behavior from a large database of customer transactions. Then the indicators are used to create a set of monitors, which profile legitimate customer behavior and indicate anomalies....}, author = {Fawcett, Tom and Provost, Foster J. }, citeulike-article-id = {788096}, journal = {Data Mining and Knowledge Discovery}, keywords = {data\_mining, detection, fraud}, number = {3}, pages = {291--316}, posted-at = {2006-08-06 17:48:54}, priority = {2}, title = {Adaptive Fraud Detection}, url = {http://citeseer.ist.psu.edu/fawcett97adaptive.html}, volume = {1}, year = {1997} }

TY - JOUR ID - citeulike:788096 L3 - citeulike-article-id:788096 TI - Adaptive Fraud Detection JF - Data Mining and Knowledge Discovery VL - 1 IS - 3 SP - 291 EP - 316 N2 - . One method for detecting fraud is to check for suspicious changes in user behavior. This paper describes the automatic design of user profiling methods for the purpose of fraud detection, using a series of data mining techniques. Specifically, we use a rule-learning program to uncover indicators of fraudulent behavior from a large database of customer transactions. Then the indicators are used to create a set of monitors, which profile legitimate customer behavior and indicate anomalies.... KW - data_mining KW - detection KW - fraud AU - Fawcett, Tom AU - Provost, Foster PY - 1997/// UR - http://citeseer.ist.psu.edu/fawcett97adaptive.html ER -