## 5 Blockchain-Based Supply Chain Security Solutions and Integration Models
### Data Privacy with Zero-Knowledge Proof (ZKP) and Confidential Transactions
#### 5.3.2 Architectural Model for Cross-Chain Supply Chains and Smart Contract Design  
As supply chains evolve into decentralized, multi-stakeholder ecosystems, ensuring interoperability between different blockchain platforms has become a functional necessity. Traditional single-chain deployments fall short when actors operate on separate permissioned and permissionless networks. Figure 8 presents a proposed conceptual cross-chain architecture that facilitates secure and verifiable data exchange between heterogeneous blockchain networks through a Chainlink bridge and ZKP validation mechanisms. This architecture operationalizes the core principles of security, traceability, and integrity (STI) within real-world supply chain contexts [87,89]. In this model, data flows between distinct blockchain domains are mediated by the bridge, which serves as a transport and interoperability layer. Information such as inventory records, production details, delivery confirmations, and payment requests can be exchanged across chains through cryptographically verified oracle inputs, ensuring accurate and trusted data transfer [55,56]. The ZKP Validator ensures that transactions are validated without exposing sensitive data, preserving commercial confidentiality and enabling secure contract enforcement. This mechanism, depicted as the ZKP Validator layer in the center of the architecture, also reduces reliance on trusted intermediaries and strengthens the privacy model [87,89,90,91]. The architecture embeds the three fundamental principles of STI as follows:  
* Security is enforced through cryptographic mechanisms and ZKP-based validation, ensuring that data remain tamper-proof and accessible only to authorized parties during cross-chain operations [91,92]. While platforms like Hyperledger Fabric natively support \begin{table}
\begin{tabular}{l l l l l l l} \hline \hline
**System** & **Oracle** & **Attack Risk** & **TPS** & **Delay (ms)** &
\begin{tabular}{l} **STI** \\ **Alignment** \\ \end{tabular} & **SCM Suitability** \\ \hline Chainlink Bridge & Moderate & High (3.1) & 30 & 140 & S/\(-\)/T & Moderate \\ Polkadot XCMP & High & Medium (2.5) & 1000 & 80 & S/T/I & High \\ Cosmos IBC & High & Low (2.2) & 800 & 50 & S/T/I & High \\ ZKP-Based & Very High & Very Low (1.2) & 100 & 180 & S/\(-\)/I & Moderate–High \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Cross-chain interoperability comparison for SCM. authentication and access control, this model incorporates additional authentication and access control mechanisms, explicitly illustrated in the center of the architecture, to ensure secure and policy-compliant data exchange at the cross-chain layer. These controls are especially critical at the bridge and ZKP validation stages, where heterogeneous blockchain systems interact and trust boundaries must be enforced. * Traceability is achieved by maintaining end-to-end audit trails, enabling all stakeholders to track assets, documents, and transactional states across multiple chains in real time [87, 89]. * Integrity is preserved via immutable ledger entries and consistency validations, ensuring the accurate reconciliation of supply chain activities [4, 43]. This model supports hybrid ecosystems where different organizations retain their preferred blockchain infrastructure while maintaining interoperability, visibility, and regulatory compliance across the network [48]. To further clarify the operational flow of the cross-chain supply chain architecture demonstrated in Figure 8, this section introduces a set of representative pseudocode functions executed on both permissioned and permissionless blockchain platforms. These logic components embody the automation backbone of decentralized supply chain ecosystems, handling verification, logging, validation, and payment release processes across blockchain domains. On the Hyperledger Fabric side, internal functions, such as _verifyOrder_() and _logProduction_(), ensure the correctness of orders and the integrity of production events, protecting private business logic from external exposure.