【Author】
Pranto, Tahmid Hasan; Noman, Abdulla All; Rahaman, Mustafizur; Haque, A. K. M. Bahalul; Islam, A. K. M. Najmul; Rahman, Rashedur M.
【Source】CYBERNETICS AND SYSTEMS
【Abstract】E-commerce platforms have made our life easier and bought plenty of advantages too. However, due to fraud and scams, trust is a concern while buying products online. In this study, we proposed a blockchain-based architecture for the e-commerce sector where data mining technology is used to detect fraudulent users by generating precise and effective rules, and smart contracts are used for enforcement and functionality management within the blockchain network. Our data mining approach yielded a competitive accuracy, precision, recall, and f1-measure of over 99% compared to the state-of-the-art. High performing rules are further tested for ten simulated cycles under completely unseen data to test their rigidity in a real-time scenario. Details analysis of delineation (if any) in rule antecedents has also been analyzed for these cycles. Tested and selected rules are stored in smart contracts deployed within blockchain network for security and immutability. For ensuring strict order criteria maintenance, better return policy, authentic review and scam avoidance, two smart contracts have been written which implement seller reputation mechanism and authentic review maintenance while safeguarding the seller from intentional defaming too. Altogether, the goal of this study is to establish a balance between all the parties within an e-commerce platform so that everyone's right is protected, money is safe and resources are not exploited.
【Keywords】Blockchain; smart contract; data mining; e-commerce; scam prevention; fraud detection
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