Abstract
With the continuous improvement and growth at a rapid pace in the utility of mobile banking payment technologies, fraudulent mobile banking transactions are being multiplied using bleeding-edge technologies sharply and a significant economic loss is made every year around the world. Phishers seek new vulnerabilities with every advance in fraud prevention and have become an even more pressing issue of security challenges for banks and financial institutions. However, researchers have focused mainly on the prevention of fraudulent transactions on the online banking system. This paper proposes a new anti-phishing model for mobile banking systems at the transaction level (AntiPhiMBS-TRN) that mitigates fraudulent transactions in the mobile banking payment system. This model applies a unique id for the transactions and an application id for the bank application known to the bank, bank application, users, and the mobile banking system. In addition, AntiPhiMBS-TRN also utilizes the international mobile equipment identity (IMEI) number of the registered mobile device to prevent fraudulent transactions. Phishers cannot execute fraudulent transactions without knowing the unique id for the transaction, application id, and IMEI number of the mobile device. This paper employs a process meta language (PROMELA) to specify system descriptions and security properties and builds a verification model of AntiPhiMBS-TRN. Finally, AntiPhiMBS-TRN is successfully verified using a simple PROMELA interpreter (SPIN). The SPIN verification results prove that the proposed AntiPhiMBS-TRN is error-free, and banks can implement the verified model for mitigating fraudulent transactions in the mobile banking system globally.
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Thakur, T.N., Yoshiura, N. (2022). AntiPhiMBS-TRN: A New Anti-phishing Model to Mitigate Phishing Attacks in Mobile Banking System at Transaction Level. In: Nguyen, N.T., Tran, T.K., Tukayev, U., Hong, TP., Trawiński, B., Szczerbicki, E. (eds) Intelligent Information and Database Systems. ACIIDS 2022. Lecture Notes in Computer Science(), vol 13758. Springer, Cham. https://doi.org/10.1007/978-3-031-21967-2_48
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