Fraud Detection in Credit Card Transactions; Using Parallel Processing of Anomalies in Big Data | ||
| Journal of Information Technology Management | ||
| مقاله 81، دوره 8، شماره 3، 2016، صفحه 477-498 اصل مقاله (415.14 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/jitm.2016.57818 | ||
| نویسندگان | ||
| Mohammad Reza Taghva* 1؛ Taha Mansouri2؛ Kamran Feizi3؛ Babak Akhgar4 | ||
| 1Associate Prof, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran | ||
| 2Ph.D. Candidate in Information Technology Management, Allameh Tabataba’i University, Tehran, Iran | ||
| 3Prof, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran | ||
| 4Prof, Sheffield Hallam University, Sheffield, England | ||
| چکیده | ||
| In parallel to the increasing use of electronic cards, especially in the banking industry, the volume of transactions using these cards has grown rapidly. Moreover, the financial nature of these cards has led to the desirability of fraud in this area. The present study with Map Reduce approach and parallel processing, applied the Kohonen neural network model to detect abnormalities in bank card transactions. For this purpose, firstly it was proposed to classify all transactions into the fraudulent and legal which showed better performance compared with other methods. In the next step, we transformed the Kohonen model into the form of parallel task which demonstrated appropriate performance in terms of time; as expected to be well implemented in transactions with Big Data assumptions. | ||
| کلیدواژهها | ||
| Big data؛ Credit cards؛ Fraud detection؛ Kohonen neural network | ||
| مراجع | ||
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آمار تعداد مشاهده مقاله: 4,995 تعداد دریافت فایل اصل مقاله: 2,463 |
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