## 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
Machine learning algorithms can identify vulnerabilities within smart contracts and proactively detect potential threats, optimizing intervention mechanisms. Integrating AI-supported security solutions into blockchain systems will enable proactive threat management, thereby establishing more secure supply chain structures [73, 74, 75]. On the other hand, advancements in quantum computing technology represent a substantial threat to existing blockchain security systems. The potential of quantum computers to break classical encryption methods poses a significant risk to blockchain networks [48, 86]. Therefore, developing solutions based on post-quantum cryptography is necessary to make blockchain systems resistant to quantum attacks. New-generation cryptographic approaches, such as lattice-based encryption and quantum-resistant signatures, will play a critical role in ensuring the long-term sustainability of blockchain security [87, 89]. In the context of quantum threats, post-quantum cryptography (PQC) stands out as a critical solution to protect blockchain-based systems against potential attacks from quantum computers. PQC algorithms are designed to remain secure, even in the presence of quantum adversaries, and are generally categorized into lattice-based, hash-based, multivariate polynomial, and code-based cryptography. Prominent examples include CRYSTALS-Kyber for key encapsulation, CRYSTALS-Dilithium for digital signatures, and SPHNCS+, a stateless hash-based signature scheme. These algorithms are currently undergoing standardization by NIST and are considered promising candidates for enabling quantum-resistant security in blockchain architectures [88, 89, 90]. In blockchain-based supply chain management systems, the long-term integrity and confidentiality of traceability records are of paramount importance. Therefore, adopting quantum-resistant cryptographic structures, particularly in permissioned networks expected to operate over extended periods, ensures sustainable data security against future quantum-era threats [89, 90]. Furthermore, some studies have conducted performance comparisons of zero-knowledge proof protocols, such as zk-SNARK, zk-STARK, and Bulletproof, in the context of post-quantum security, discussing their potential integration into future blockchain systems [72, 73]. Finally, establishing regulatory frameworks and enhancing cross-sector collaboration are critical components for securing blockchain-based supply chains. Developinginternational security standards will ensure compliance and enhance technology reliability. Encouraging academic research and industry collaboration will accelerate blockchain adoption, creating a robust ecosystem for supply chain security [86, 91, 93]. ## 7 Discussions

Having examined the technical and sectoral dimensions of blockchain in SCM, this section synthesizes the key insights and presents broader discussions on integration, sustainability, and security trade-offs. ### Integration of Blockchain into Existing Supply Chains: Practical Complexities

Although blockchain offers convincing advantages in terms of security, traceability, and data integrity, its integration into existing supply chains remains highly complex. In particular, centralized ERP systems and traditional databases already used in supply chain processes are not inherently compatible with blockchain infrastructures [1, 26]. This misalignment requires significant infrastructure transformations and extensive inter-organizational collaboration. Furthermore, since many actors in the supply chain are SMEs, a digital divide emerges due to disparities in technical capabilities and investment resources [6]. These constraints hinder the holistic implementation of blockchain systems across the entire supply chain. ### Privacy vs. Transparency Paradox

Supply chains are typically complex, multi-actor systems expected to remain both transparent and competitive. However, the level of transparency required to enable traceability may risk disclosing trade secrets or sensitive business information.