An Intelligent System for Fraud Detection in Coin Futures Market’s Transactions of Iran Mercantile Exchange Based on Bayesian Network

• Main Authors: Amir-Reza Abtahi, Fatemeh Elahi, Reza Yousefi-Zenouz
• Format: Article
• Language: fas
• Published: University of Tehran 2017-03-01
• Series: Journal of Information Technology Management
• Subjects: Bayesian network; Fraud detection; Futures contract; Induction behavior; Mercantile exchange
• Online Access: https://jitm.ut.ac.ir/article_60680_26aa06de30a6257fb58215616a88d6ba.pdf

In order to gain more illicit profit, some traders in the stock market try to make a targeted impact on prices by placing fake orders and false advertising. Due to the high customer population, it is not possible to discover these frauds using traditional methods. The present study seeks to provide a system for preventing the frauds in future market-trading coins based on Bayesian classifier model for Iran Mercantile Exchange. The proposed model has polynomial time complexity and high accuracy because of considering important dependencies among different features of data. The primary labeling of data has been done by Kmeans clustering. The test of model shows 94.55 percent similarity between model's output and labeled data. Using this system can helps to identify the fraudulent from non-fraudulent traders.