Abstract
The conventional financial frameworks such as the exchanges over the bank counter with a passbook are upgraded by adding the components of electronic banking, all the bank exchanges/transaction are made possible over the Internet with the progression of data and the corresponding innovation. Nonetheless, there are significant risks associated with this innovation, such as banking fraud. Hence, to fabricate trust among banking clients, it is vital to build security systems. In electronic banking, security systems basically centre on demonstrating a solid framework for the web-based exchange, particularly client validation. Numerous experts have proposed various models for web-based client access validation in the financial industry. A large portion of the research depends on the conventional type of username and secret key, yet with the differing systems of secret key structures. For example, secret phrase in erratic worth, secret key in erratic worth via obtained channel, and biometric preferred finger impression acknowledgement, voice acknowledgement, or retina acknowledgement. This paper has examined the existing client access for Internet banking based on mobile phones. The elements of the SIM card and the attributes portable of the SIM card are portrayed. Cloning, a danger to the SIM card is additionally portrayed. Discoveries show that all the security models for online client access contain secret words such as worth, biometric, or PIN. In this manner, none of the current client accesses proposed the possibility of the client access in the light of the International Mobile Equipment Identity (IMEI) number to strengthen the security of the client access. The proposed research work is more focused on security the mobile payment by utilizing the IMEI.
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Thanks to the Department of Computer Science and Engineering, Hindustan Institute of Technology and Science, Chennai, India.
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Kathiravan, M., Sambath, M., Bhuvaneshwari, B., Nithya Krishna, S., Jeshwin, W., Babu, N. (2023). Improved Security on Mobile Payments Using IMEI Verification. In: Shakya, S., Du, KL., Ntalianis, K. (eds) Sentiment Analysis and Deep Learning. Advances in Intelligent Systems and Computing, vol 1432. Springer, Singapore. https://doi.org/10.1007/978-981-19-5443-6_16
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