Analysis and design of secure distributed blockchain based framework for supply chain management

Abstract

The organizations have struggled to monitor their products, especially in supply chain management during the early period. During the supply chain process, the attackers mixed counterfeit along with original items into the market. Therefore, customers were compelled to buy low-quality items at higher prices and are occasionally susceptible to health and safety hazards due to fake products. Though traditional anti-counterfeit systems solutions are in existence to detect counterfeit products, their uses became sterile due to their centralized characteristic. Some of the vital issues of centralized systems are; scalability, fault tolerance, single point of failure and third party. Therefore, it was believed that the blockchain solutions, may rightly address those difficulties. Blockchain could be employed in many applications including healthcare, finance, supply chain, and voting system due to its unique characteristics like immutability, decentralized, security, and consensus. Blockchain has some security challenges during transactions and it is vulnerable to attacks such as tag cloning attack, eavesdropping attack, and block withholding attacks. Therefore, this study has proposed a secure distributed blockchain based framework for Supply Chain Management (SCM). A Blockchain based Anonymous Anti-Counterfeit (BA2C) supply chain module developed based on RFID and blockchain technology in the context stated above. All transactions were optimized using Ethereum with Proof of Authority (PoA) consensus. The proposed module has been tested on transaction cost, latency, and throughput. Further, a novel authentication approach utilizing Physical Unclonable Functions (PUFs) is proposed to address the challenges of traceability and authentication while gathering product data via IoT devices. Consequently, a novel Proof-of-Improved-Participation (PoIP) consensus mechanism is presented which selects genuine peers for mining process.