Sequential pattern mining approach for personalized fraudulent transaction detection in online banking

HIGHLIGHTS

  • who: Junghee Kim and collaborators from the Department of Industrial Engineering, Yonsei University, Seoul, Korea have published the paper: Sequential Pattern Mining Approach for Personalized Fraudulent Transaction Detection in Online Banking, in the Journal: Sustainability 2022, 14, x FOR PEER REVIEW Sustainability 2022, Sustainability 2022, 14, 14, 9791 x FOR PEER REVIEW of /2022/
  • what: The authors propose a personalized alarm model to detect frauds in online banking transactions using sequence pattern mining on each user`s normal transaction log. The authors focused on the fact that fraudulent transactions are very different from each user . . .

     

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