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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، آذر 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 | ||
| عنوان مقاله [English] | ||
| کشف تقلب در تراکنشهای کارتهای بانکی با استفاده از پردازش موازی ناهنجاری در بزرگ‌داده | ||
| نویسندگان [English] | ||
| محمدرضا تقوا1؛ طاها منصوری2؛ کامران فیضی3؛ بابک اخگر4 | ||
| 1دانشیار گروه مدیریت صنعتی، دانشکدۀ مدیریت و حسابداری دانشگاه علامه طباطبایی، تهران، ایران | ||
| 2دانشجوی دکتری مدیریت فناوری اطلاعات، دانشکدۀ مدیریت و حسابداری دانشگاه علامه طباطبایی، تهران، ایران | ||
| 3استاد گروه مدیریت صنعتی دانشکدۀ مدیریت و حسابداری دانشگاه علامه طباطبایی، تهران، ایران | ||
| 4استاد گروه انفورماتیک، دانشگاه شفیلد هلم، شفیلد، انگلستان | ||
| چکیده [English] | ||
| با رشد روز‌افزون استفاده از کارتهای الکترونیکی، بهخصوص در صنعت بانکی، حجم تراکنش با این کارتها نیز به‌سرعت افزایش پیدا کرده است. به‌علاوه، ذات مالی این کارتها سبب ایجاد مطلوبیت تقلب در این حوزه شده است. تحقیق حاضر با رویکرد پردازش موازی و راهحل نگاشت کاهش، از شبکۀ عصبی مدل کوهونن برای کشف ناهنجاری در تراکنش کارتهای بانکی استفاده کرده است. برای این منظور، در مرحلۀ نخست راهحلی برای طبقهبندی تراکنشها به تقلبآمیز و قانونی پیشنهاد شد که نسبت به روشهای دیگر عملکرد بهتری از خود نشان داد. در مرحلۀ بعد، روش پیشنهادی بهدستآمده از تبدیل شبکۀ کوهونن به فرم استفاده‌شدۀ نگاشت کاهش، توانست قابلیت مناسبی را از نظر زمان اجرا به نمایش بگذارد؛ بهطوریکه انتظار میرود در تراکنشهایی با مفروضات بزرگ‌داده به‌خوبی پیادهسازی شود. | ||
| کلیدواژه‌ها [English] | ||
| بزرگ‌داده, کارتهای بانکی, کشف تقلب, مدل شبکۀ عصبی کوهونن | ||
| مراجع | ||
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