Transaction-Based Blockchain Systems Security Improvement Employing Micro-Segmentation Controlled by Smart Contracts and Detection of Saddle Goatfish

One of the most significant concerns in e-banking is the security of financial transactions. Furthermore, it is a major issue if it is never under control especially since security should be a combination of fast and sturdy characteristics, which the previous studies suffered from. Our research aims to enhance the way banks handle the security of financial transactions. To concentrate on security, this study employs the idea of micro-segmenting the system into several zones, each with its own set of rules and limitations. In order to verify the identity of the customer, a smart contract monitors the implementation of these rules and determines if they have been obeyed. First, the kind of e-banking request was specified using the two-phase commit procedure (2PC). Following this, each sort of e-transaction process was isolated using the micro-segmentation principle in a distinct segment, which was subsequently compressed using the Zstd method. After that, it was decided whether or not the smart contract conditions had been met optimally by applying the yellow saddle goatfish algorithm (YSGA). Finally, if the customer is permitted, then the entire transaction process is kept in the Blockchain’s main ledger and is safeguarded by a unique hash, our system has been tested against a few recent well-known assaults/attacks and has proven to be able to defeat them. In terms of performance evaluation, we obtained: An execution time ratio between 0.001 nanoseconds and 0.06 nanoseconds, a complexity ratio of 3.75% which is appropriate with a system like our proposed one that has many layers, where the complexity ratio indicates the degree to which the layers interact with each other without causing unexpected or incomprehensible results, and finally we obtained a percentage between 150 KB and 1050 KB for the total storage consumed by the system, which is considered low compared to art-of-state research. Thus, our proposed system can be highly acceptable in banking sector applications.