Enhanced Fraud Miner: Credit Card Fraud Detection using Clustering Data Mining Techniques

نویسندگان

  • Mohamed Hegazy
  • Ahmed Madian
  • Mohamed Ragaie
چکیده

This paper aimed to build unified pattern per customer not only represent normal behavior but also Fraud pattern that’s represented previously and confirmed as fraud transactions that’s facilitate studding fraudsters behavior. An enhancement for the proposed algorithm of Fraud Miner has been proposed. This enhancement involves introducing LINGO clustering Data mining algorithm by replacing Apriori algorithm used in Fraud Miner for Frequently Pattern creation and facilitate summarize customer previous behavior either within his Legal or Fraud transactions. Using this algorithm provide more chance for easily fraud detection as the fraudsters always behaving same as customer behaviors instead of study fraudster behavior the customer frequent behavior will be identified from his legal or previously confirmed transactions being fraud. A performance comparison with other algorithms has been carried out.

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تاریخ انتشار 2016