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결제로그 분석 및 데이터 마이닝을 이용한 이상거래 탐지연구 조사

A Survey of Fraud Detection Research based on Transaction Analysis and Data Mining Technique

김하나|이태진|신영상|김휘강|정성훈
한국정보보호학회 (Korea Institute Of Information Security And Cryptology)|2015.12|정보보호학회논문지 (Journal of The Korea Institute of Information Security and Cryptology)|제25권 제6호|pp. 1525-1540|DOI http://dx.doi.org/10.13089/JKIISC.2015.25.6.1525

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참고문헌

키워드

SurveyCategorizationData MiningFraud DetectionCredit CardFinancial Fraud
주제분류컴퓨터학

초록

금융 산업과 IT 기술의 결합으로 지불 방법이 간편화됨에 따라 소비자의 지불 수단이 현금 결제에서 신용카드, 모바일 소액결제, 앱카드 등을 이용한 전자결제로 변화되고 있다. 이에 전자금융결제를 악용하여 이상거래를 시도하는 사례가 증가하는 추세로, 금융사는 이상거래로부터 소비자를 보호하기 위해 FDS(Fraud Detection System) 를 구축하고 있다. 이상거래 탐지 시스템은 실시간으로 이용자 정보와 결제 정보를 분석하여 높은 정확도로 이상거래를 식별하는 것이 목표이다. 본 연구에서는 결제로그 분석 및 데이터 마이닝을 이용한 이상거래 탐지 연구 동향을조사하였으며, 이상거래 탐지에 사용된 데이터 마이닝 알고리즘을 정리하고 이상거래 탐지 연구를 사용된 데이터셋, 알고리즘, 연구 관점으로 분류하였다.

Abstract

Due to a rapid advancement in the electronic commerce technology, the payment method varies from cash to electronic settlement such as credit card, mobile payment and mobile application card. Therefore, financial fraud is increasing notably for a purpose of personal gain. In response, financial companies are building the FDS (Fraud Detection System) to protect consumers from fraudulent transactions. The one of the goals of FDS is identifying the fraudulent transaction with high accuracy by analyzing transaction data and personal information in real-time. Data mining techniques are providing great aid in financial accounting fraud detection, so it have been applied most extensively to provide primary solutions to the problems. In this paper, we try to provide an overview of the research on data mining based fraud detection. Also, we classify researches under few criteria such as data set, data mining algorithm and viewpoint of research.

참고문헌 (38)

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