Secure Channel for Financial Transactions in Cloud Environment Using Blockchain Technology

Abstract

The progression of digital technology impacts the users to migrate from traditional financial transactions to the online transaction system for performing their financial transactions. The existence of cloud computing and its major benefit of access from anywhere promotes financial transactions. The cloud infrastructure supporting performing financial transactions deals with the huge volume of data and it is quintessential to sustain a high level of security to those sensitive credentials in the cloud storage. The conventional cryptographic algorithms hold good in providing a better level of security to the sensitive data in cloud computing but still fall back to advanced attacks against the cloud data storage. Furthermore, the employment of conventional encryption algorithms in securing the cloud data consumes huge execution time, as it has to perform the authentication check for all types of user access including legitimate and non-legitimate accesses. This research article proposes a novel methodology of incorporating blockchain technology to perform online financial transactions in cloud computing with a high level of security, availability, and reduced execution time. This research work employs Blockchain technology integrated with Elliptical Curve Cryptography (ECC) and Chaotic Map Confusion and Diffusion algorithm to perform secured transactions over a cloud network. The interpretation of the proposed method contributes to better performance in the aforementioned parameters than the existing methodologies. The proposed framework is compared with the conventional method of online transactions using Multi-Factor Authentication (MFA) encompassing the Elliptical Curve Cryptography (ECC). The performance analysis proves that the proposed framework exhibits a high level of security along with reduced computational time, encryption, and decryption cost. The proposed work is interpreted with sample dataset and the computational time is reduced.