An Enhanced Security System Using Blockchain Technology for Strong FMC Relationship

Blockchain technology is a shared database of logs of all consumer transactions which are registered on all machines on a network. Both transactions in the system are carried out by consensus processes and to preserve confidentiality all the files contained cannot be changed. Blockchain technology is the fundamental software behind digital currencies like Bitcoin, which is common in the marketplace. Cloud computing is a method of using a network of external machines to store, monitor, and process information, rather than using the local computer or a local personal computer. The software is currently facing multiple problems including lack of data protection, data instability, and reliability. This paper aims to give the highest security for multiple user environments in cloud for storing and accessing the data in blocks. The users who are legitimate are only allowed for storing and accessing the data as like a secured block chain approach. As like the Blockchain which does not require a centralized system for transactions, the proposed system is also independent on centralized network interface. The decentralized system is developed in such a way to avoid counterfeiting. The system enables the fabricator to spend less or null resources to perform the validations for its direct operated stores. This ensures the product fabricator to avoid the circulation of its duplicate products. The customer as an end-user is also ensured to have only the genuine products from the fabricator. The Fabricator (F), Merchant (M) and consumer (C) forms an interconnected triangular structure without allowing any counterfeiting agents in their secured cloud chain. The proposed approach provides the stability in the security system of the cloud using the chaining mechanism within different blocks at each node. It takes roughly 4.7, 6.2, and 7.5 ms, respectively, to register each node in the proposed system for 5, 10, and 15 nodes. The overall registration time for each scenario is 11.9, 26.2, and 53.1 ms, despite the fact that each node's registration time was greatest for 10 nodes. By looking at the data, it's clear that the number of nodes is a function of time.