Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/11900
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dc.contributor.authorRaval, Jay-
dc.date.accessioned2023-08-18T08:59:18Z-
dc.date.available2023-08-18T08:59:18Z-
dc.date.issued2023-06-01-
dc.identifier.urihttp://10.1.7.192:80/jspui/handle/123456789/11900-
dc.description.abstractIn this paper, we present an artificial intelligence(AI) and blockchain-based credit card fraud detection system for detecting fraud transactions in the dataset. This dataset has 284808 rows P with 31 columns Q and 0.17 % fraud class data. In the data preprocessing step, clean the data and normalized the feature. For a select important feature, we use explainable artificial intelligence(XAI) to get the highest priority feature in the dataset. Long short-term memory (LSTM) is used to detect fraud in the system and gives better accuracy. Blockchain is a decentralized system to secure the transaction of the system using smart contracts and an InterPlanetary File System(IPFS). After all processes, the LSTM gives 99.8% accuracy with using XAI. Also, present the comparison between two LSTM results with and without using XAI. Then we save the non-fraud transaction data using smart contracts and blockchain. Finally, we conclude our proposed system architecture with the results. Keywords: Explainable artificial intelligence, credit card frauds, deep learning, long short-term memory, fraud classificationen_US
dc.publisherInstitute of Technologyen_US
dc.relation.ispartofseries21MCED18;-
dc.subjectComputer 2021en_US
dc.subjectProject Report 2021en_US
dc.subjectComputer Project Reporten_US
dc.subjectProject Reporten_US
dc.subject21MCEen_US
dc.subject21MCEDen_US
dc.subject21MCED18en_US
dc.subjectCE (DS)en_US
dc.subjectDS 2021en_US
dc.titleArtificial Intelligence and Blockchain-based Financial Fraud Detectionen_US
dc.typeDissertationen_US
Appears in Collections:Dissertation, CE (DS)

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