Privacy preserving ZK-STARK based blockchain for agriculture food supply chain

Abstract

The blockchain-based applications such as food supply chain (FSC), healthcare are becoming increasingly popular due to their decentralized nature, distributed structure, and the ability to track products. Still, there are concerns regarding the privacy of transacted data, including personal identities, as all transactions are recorded on a ledger accessible to participating nodes. Existing technologies of privacy preservation are vulnerable to quantum attacks, which will pose a significant threat to blockchain applications in the future. To address this, a proposed model uses modified zero-knowledge scalable transparent argument of knowledge (ZK-STARK) in the blockchain FSC by utilizing three different polynomial interpolation methods. Performance measurements indicate that the fast fourier transform (FFT) outperforms the others. Unlike ZK-SNARK, ZK-STARK does not require a trusted setup, makes scalable and transparent. By defending against quantum attacks, this model enhances the security of the blockchain system. The blockchain-based FSC is implemented using hyperledger composer, with all entities completing transactions privately through ZK-STARK and smart contracts. But, ZK-STARK may add performance overhead into the blockchain FSC. Future work will aim to reduce the performance overhead of ZK-STARK, decide which operations should be off-chain or on-chain, and compare the performance of this new model to the existing system.