Towards Transparency In Fuel Ecosystem: A Blockchain And DL Based Model For Bunker Fuel Traceability And Environmental Compliance

Abstract

Ensuring the authenticity and quality of bunker fuel continues to remain a significant challenge in maritime trade, especially with issues regarding fuel adulteration, fraud and inadequate supply chain management persisting. The DNA- Blockchain based AI assisted Traceability (D-BAIT) study proposes an advanced framework integrating DNA tagging, blockchain technology and Deep Learning algorithms to establish a secure, transparent and automated fuel traceability system. DNA markers act as tamper-proof unique identifiers which is verified using Next-Generation Sequencing (NGS) and Polymerase Chain Reaction (PCR)-based DNA authentication by embedding them in fuel at the point of origin, thereby ensuring real-time validation of authenticity. The verification results are then recorded on a permissioned blockchain, providing immutability, decentralized access and secure transactions for key stakeholders, including ship operators, regulators and insurers. To enhance fraud detection and operational efficiency, DL algorithms are utilised along with blockchain transaction monitoring through Graph Neural Networks (GNNs) and LSTMs to leverage real-time anomaly detection in blockchain transactions, thus helping to identify suspicious fuel transactions. Additionally, smart contracts deployed on the Ethereum Virtual Machine (EVM) on cross-border payments further verifies fuel authenticity.