Title :
Fraud Detection: From Basic Techniques to a Multi-Agent Approach
Author :
Buoni, Alessandro
Author_Institution :
Inst. for Adv. Manage., Turku Center for Comput. Sci., Turku, Finland
Abstract :
According to KPMG figures, fraud represents a serious economical problem, which has been studied in different ways due to the fact that fraudsters are benefiting from the fast development of ICT and are developing their techniques. In this paper, after summarizing different fraud detection methods and tools proposed in the literature like meta-rules and tree-based detection, we will introduce a multi-agent system, called FIDES, which integrates the computational power of data mining tools and attack trees with experts´ judgments negotiated through a Delphi-based system. Two scenarios are described: in the first one FIDES, supported by cause-effect diagrams, is used to classify alarms generated by the system to help the experts to focus on the real dangerous ones; in the second one FIDES is used in a proactive way in order to block or prevent human based frauds.
Keywords :
data mining; decision support systems; fraud; multi-agent systems; security of data; Alessandro KPMG figures; Delphi-based system; ICT; attack trees; cause-effect diagrams; data mining tools; fraud detection methods; fraud interactive decision expert system; human based fraud prevention; meta-rules; multi-agent approach; tree-based detection; Artificial neural networks; Decision support systems; Filtering; Forensics; Multiagent systems; Pediatrics; Security;
Conference_Titel :
Management and Service Science (MASS), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5325-2
Electronic_ISBN :
978-1-4244-5326-9
DOI :
10.1109/ICMSS.2010.5577218
