Applying Extensions of Evidence Theory to Detect Frauds in Financial Infrastructures
The Dempster-Shafer (DS) theory of evidence has significant weaknesses when dealing with conflicting information sources, as demonstrated by preeminent mathematicians. This problem may invalidate its effectiveness when it is used to implement decision-making tools that monitor a great number of para...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-10-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2015/980629 |
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| _version_ | 1849412754755026944 |
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| author | Luigi Coppolino Salvatore D'Antonio Valerio Formicola Luigi Romano |
| author_facet | Luigi Coppolino Salvatore D'Antonio Valerio Formicola Luigi Romano |
| author_sort | Luigi Coppolino |
| collection | DOAJ |
| description | The Dempster-Shafer (DS) theory of evidence has significant weaknesses when dealing with conflicting information sources, as demonstrated by preeminent mathematicians. This problem may invalidate its effectiveness when it is used to implement decision-making tools that monitor a great number of parameters and metrics. Indeed, in this case, very different estimations are likely to happen and can produce unfair and biased results. In order to solve these flaws, a number of amendments and extensions of the initial DS model have been proposed in literature. In this work, we present a Fraud Detection System that classifies transactions in a Mobile Money Transfer infrastructure by using the data fusion algorithms derived from these new models. We tested it in a simulated environment that closely mimics a real Mobile Money Transfer infrastructure and its actors. Results show substantial improvements of the performance in terms of true positive and false positive rates with respect to the classical DS theory. |
| format | Article |
| id | doaj-art-54bde2fd8fbf41eebe8b819c003bf9da |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2015-10-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-54bde2fd8fbf41eebe8b819c003bf9da2025-08-20T03:34:21ZengWileyInternational Journal of Distributed Sensor Networks1550-14772015-10-011110.1155/2015/980629980629Applying Extensions of Evidence Theory to Detect Frauds in Financial InfrastructuresLuigi CoppolinoSalvatore D'AntonioValerio FormicolaLuigi RomanoThe Dempster-Shafer (DS) theory of evidence has significant weaknesses when dealing with conflicting information sources, as demonstrated by preeminent mathematicians. This problem may invalidate its effectiveness when it is used to implement decision-making tools that monitor a great number of parameters and metrics. Indeed, in this case, very different estimations are likely to happen and can produce unfair and biased results. In order to solve these flaws, a number of amendments and extensions of the initial DS model have been proposed in literature. In this work, we present a Fraud Detection System that classifies transactions in a Mobile Money Transfer infrastructure by using the data fusion algorithms derived from these new models. We tested it in a simulated environment that closely mimics a real Mobile Money Transfer infrastructure and its actors. Results show substantial improvements of the performance in terms of true positive and false positive rates with respect to the classical DS theory.https://doi.org/10.1155/2015/980629 |
| spellingShingle | Luigi Coppolino Salvatore D'Antonio Valerio Formicola Luigi Romano Applying Extensions of Evidence Theory to Detect Frauds in Financial Infrastructures International Journal of Distributed Sensor Networks |
| title | Applying Extensions of Evidence Theory to Detect Frauds in Financial Infrastructures |
| title_full | Applying Extensions of Evidence Theory to Detect Frauds in Financial Infrastructures |
| title_fullStr | Applying Extensions of Evidence Theory to Detect Frauds in Financial Infrastructures |
| title_full_unstemmed | Applying Extensions of Evidence Theory to Detect Frauds in Financial Infrastructures |
| title_short | Applying Extensions of Evidence Theory to Detect Frauds in Financial Infrastructures |
| title_sort | applying extensions of evidence theory to detect frauds in financial infrastructures |
| url | https://doi.org/10.1155/2015/980629 |
| work_keys_str_mv | AT luigicoppolino applyingextensionsofevidencetheorytodetectfraudsinfinancialinfrastructures AT salvatoredantonio applyingextensionsofevidencetheorytodetectfraudsinfinancialinfrastructures AT valerioformicola applyingextensionsofevidencetheorytodetectfraudsinfinancialinfrastructures AT luigiromano applyingextensionsofevidencetheorytodetectfraudsinfinancialinfrastructures |