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A Delphi-Based Approach to Fraud Detection Using Attack Trees and Fuzzy Numbers

Alessandro Fedrizzi Buoni, Jozsef Mario Mezei, A Delphi-Based Approach to Fraud Detection Using Attack Trees and Fuzzy Numbers. In: Proceeding of the IASK International Conferences, 2010.

Abstract:

The fraud surveys carried out in the last five years by leading international consulting companies demonstrate that fraud is an increasing phenomenon depending most of all on behavioral aspects. Therefore, when addressing fraud detection processes the adoption of traditional statistical techniques comes out to be not as adequate as those based on the evaluations of experts working in a multiagent framework. In this paper we introduce a multiagent system called Fraud Interactive Decision Expert System (FIDES), which puts more emphasis on the evaluation of behavioral aspects of fraud detection according to the judgments expressed by two groups of experts, inspectors and auditors respectively. FIDES combines think-maps, attack trees and fuzzy numbers under a Delphi-based team work support system and offers to the users a suitable way to better understand and manage fraud schemes.

BibTeX entry:

@INPROCEEDINGS{inpBuMa10a,
  title = {A Delphi-Based Approach to Fraud Detection Using Attack Trees and Fuzzy Numbers},
  booktitle = {Proceeding of the IASK International Conferences},
  author = {Buoni, Alessandro Fedrizzi and Mario Mezei, Jozsef},
  year = {2010},
}

Belongs to TUCS Research Unit(s): Other

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