DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Yoon, Hyun Soo | - |
dc.contributor.advisor | 윤현수 | - |
dc.contributor.author | Lee, Nam Sub | - |
dc.date.accessioned | 2018-06-20T06:24:22Z | - |
dc.date.available | 2018-06-20T06:24:22Z | - |
dc.date.issued | 2017 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=718733&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/243453 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 전산학부, 2017.8,[iii, 22 p. :] | - |
dc.description.abstract | Payment fraud in Online game is occurring frequently as real money trading market capable of selling game items in real money has emerged. In the previous research, a statistical based method to detect abnormal transactions was proposed. However, this method continues to misclassify some normal and abnormal users when their transaction statistics are similar with each other. We propose a sequence model that can overcome this problem. We also propose a new sequence model capable of reflecting purchase behavioral pattern between normal and abnormal users, so that it overcomes the problem of misclassification between normal and abnormal users with the same sequence information. In order to do that, we model the sequence of transactions with a recurrent neural network which also combines charge and purchase transaction features in single feature vector. In experiments using real data (a 483,410 transaction log) from a famous online game company in Korea, the proposed method shows a 78% recall rate with a 0.057% false positive rate. This recall rate is 7% better than current methodology utilizing transaction statistics as features. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Online Game Security▼aPayment Fraud▼aAbnormal Transaction Detection▼aSequence modeling▼aBehavioral Pattern▼aRecurrent Neural Network | - |
dc.subject | 온라인 게임 보안▼a결제 사기▼a이상거래탐지▼a순서 모델링▼a행위패턴▼a순환신경망 | - |
dc.title | Online game abnormal transaction detection based on recurrent neural network using behavioral pattern | - |
dc.title.alternative | 행위패턴을 활용한 순환신경망 기반 온라인게임이상거래탐지 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :전산학부, | - |
dc.contributor.alternativeauthor | 이남섭 | - |
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