## 5 Blockchain-Based Supply Chain Security Solutions and Integration Models
### Data Privacy with Zero-Knowledge Proof (ZKP) and Confidential Transactions
\begin{table}
\begin{tabular}{l l l l l l l l} \hline \hline
**Protocol** & **Proof Size (Byte)** & \begin{tabular}{l} **Proving Time** \\ **(ms)** \\ \end{tabular} & \begin{tabular}{l} **Verification Time** \\ **(ms)** \\ \end{tabular} & \begin{tabular}{l} **Trusted** \\ **Setup Req?** \\ \end{tabular} & \begin{tabular}{l} **Quantum** \\ **Resistant** \\ \end{tabular} & \begin{tabular}{l} **SCM Suitability** \\ \end{tabular} \\ \hline zk-SNARK & (via Rust & Language) & \begin{tabular}{l} (via Go \\ Language) \\ 1299 (15 rounds) \\ \end{tabular} & \begin{tabular}{l} (via Go \\ Language) \\ 1299 (15 rounds) \\ \end{tabular} & \begin{tabular}{l} (via Go \\ Language) \\ 1138 (15 rounds) \\ \end{tabular} & Yes & No & \begin{tabular}{l} High: compact, fast \\ verification, efficient, \\ enterprise-ready, widely \\ deployed, S/T/- \\ \end{tabular} \\ zk-STARK & 55,132 & 44,876 & 0.452 & Setup-free & Yes & \
\begin{tabular}{l} Moderate–High: \\ large size, \\ quantum-safe, S/T/I \\ Moderate–High: \\ compact, setup-free, \\ optimal for lightweight \\ SCM, -/T/- \\ \end{tabular} \\ Bulletproofs & 1249 & 3,614,500 & 1,271,200 & Setup-free & No &
\begin{tabular}{l} Higher: compact, fast \\ verification, efficient, \\ enterprise-ready, widely \\ deployed, S/T/- \\ Moderate–High: \\ large size, \\ quantum-safe, S/T/I \\ Moderate–High: \\ compact, setup-free, \\ optimal for lightweight \\ SCM, -/T/- \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Quantitative comparison of widely used ZKP protocols based on performance metrics and supply chain suitability. Figure 6: Widely used zero-knowledge proof protocols in blockchain systems. ness, no setup requirement, and ease of integration. Their classification as Moderate-High (-/T/-) reflects this contextual strength despite certain technical limitations. zk-SNARK, though lacking in transparency and quantum resistance, stands out with its ultra-compact proof size, mature tooling, and efficient verification, enabling cost-effective, fast, and scalable deployments. Its widespread adoption in real-world blockchain systems, like Ethereum and Zcash, reflects its maturity and readiness for enterprise-oriented supply chains, particularly in scenarios where efficiency and seamless integration are critical (S/T/-). Beyond protocol-level comparisons, real-world blockchain platforms such as Ethereum are integrating zk-SNARKs and related mechanisms to enhance on-chain privacy [90]. Building upon these developments, Table 8 shows recent academic studies that explore the implementation of zero-knowledge proofs within blockchain-based supply chains. Protecting commercial confidentiality in supply chain processes is critical for maintaining the competitive advantage and data security. In traditional blockchain systems, transaction data are transparently recorded, making commercial agreements, pricing policies, and supply chain information publicly visible. This exposure can enable competitors to access strategic information and allow suppliers to gain bargaining power through price comparisons. To address these risks, the confidential transactions protocol was developed, ensuring that transaction amounts and party information remain accessible only to authorized users, while independently verifying the validity of transactions. Techniques such as homomorphic encryption, Pedersen Commitments, and Bulletproofs (all forms of ZKP) preserve transaction details while ensuring blockchain reliability and integrity. Confidential transactions achieve a balance between privacy and auditability in supply chains, protecting commercial information while allowing authorized auditors to validate transactions. For instance, a large retail company's private pricing agreements with various suppliers can be secured on the blockchain, ensuring visibility exclusively to authorized parties, thus maintaining competitive advantages. Additionally, these protocols minimize data security threats such as MitM attacks, protecting sensitive information from misuse. Conse