Abstract
In the recent era, the communication network with the support of many wireless technologies is giving benefits for remote access. Such a communication model increases the flexibility for data storage with the management of network resources efficiently with the integration of the Internet of Things (IoT). Although, the industrial Internet of Things (IIoT) has enabled the development of numerous machine learning-based solutions to provide real-time applications. However, most of the solutions are not prepared to cope with heterogeneous services and the huge amount of device data in the digital world. Furthermore, conducting financial transactions over the Internet raises several security issues. Such restrictions compromise the sensitive data of financial institutions and also degrade the trust of network users in the system. Thus, this article presents a secured blockchain model for high-performance computing in a big data environment, which aims to protect the business activities for financial interaction with intelligent services of software-defined network (SDN) architecture. First, to keep the security credentials, the SDN controller creates an association between the IoT devices and maintains local and global records. Second, the machine learning approach is explored using reliable and fault-tolerant methods to support the network scalability and extract the updated routing information for transmitting financial data. The proposed protocol also provides data integrity with a high level of network availability and copes with the financial security of big data by investigating cryptographic approaches. Our proposed protocol is tested using simulation, and various experiments are performed to show its efficacy in terms of network throughput, computing overhead, data delay, response time, and dropped packets as compared to tunicate swarm algorithm-based optimized routing mechanism (TORM) and RouteChain.