International Conference on Air Defense and Security (ICADS)

Quantum-Enhanced Blockchain for Optimized Supply Chain Management: Leveraging Qaoa and Secure Transaction Protocols

L. Sherin Beevi, Ponsy R. K. Sathia Bhama, P. M. Joe Prathap, V Muthupandian

Published Feb 12, 2026• 1 citation

Abstract

A quantum-enabled blockchain architecture for secure and efficient supply chain management is created by combining quantum optimization, decentralized transaction control, and post-quantum security enforcement. Supply chain decision factors such as supplier allocation, routing optimization, and inventory coordination are framed as combinatorial optimization problems and solved using the Quantum Approximate Optimization Algorithm. The optimum decision outputs are carried out via blockchain-based smart contracts, which enable automatic validation, transparent processing, and immutable transaction storage. A quantum-resistant security layer allows for safe authentication, encrypted communication, and attackresistant transaction verification against both classical and quantum adversaries. A multi-tier simulated supply chain environment is used to evaluate system performance, which includes measures such as latency, throughput, optimization accuracy, security resilience, and operational cost. When compared to traditional supply chain and blockchain-based implementations, the results show faster convergence, lower transaction latency, more security, and greater transparency. The findings support the efficacy of combining quantum optimization, decentralized ledgers, and quantum-resilient encryption for next-generation intelligent supply chains.

DOI: 10.1109/icads69450.2026.11545470

Related papers

A Hybrid Quantum-Classical Approach for Solving QUBO Models in Blockchain-Enabled Supply Chain Inventory Management

L. Sherin Beevi, Ponsy R. K. Sathia Bhama, P. M. Joe Prathap +2 more

Managing inventory in large-scale supply chains necessitates quick, cost-effective decisions that adhere to constraints such as storage limits and variable demand. This paper describes a novel hybrid approach that uses both quantum and classical computers to tackle inventory problems structured as Quadratic Unconstrained Binary Optimization (QUBO). Each choice variable, such as restocking a product, is represented in binary form, with related costs and penalties built into the objective function. Business constraints are communicated indirectly using adjustable weights, allowing the model to remain unconstrained while discouraging unrealistic conclusions. Optimization is carried out using both classical methods like simulated annealing and quantum solvers such as D-Wave and QAOA, where a hybrid strategy selects the most viable solution. The results indicate that the hybrid system consistently produces lower total costs and better constraint compliance compared to individual solvers, especially for complex, high-dimensional datasets. To ensure secure, automated execution of these optimized decisions, a blockchain layer is introduced. Inventory actions—such as placing orders or updating stock—are carried out through smart contracts that provide tamper-proof, verifiable enforcement. By employing a lightweight Proof of Authority (PoA) mechanism, transaction validation remains fast while maintaining transparency across all nodes in the network. This integration of quantum optimization with blockchain automation enables a responsive and trustworthy framework for modern inventory management.

International Conference on Computing and Communications (COMPUTINGCON)Sep 1, 20251 citation

Quantum-Enhanced Optimization of Smart Contract Execution for Automated Financial Services

Deni Teminyan

Decentralized finance (DeFi) uses smart contracts to automate payments, lending, and asset management, but current blockchains often suffer from slow, expensive, and energy-hungry execution. In this project, I explore a quantum-enhanced optimization framework for smart contract–based financial services. The main idea is to treat gas use, transaction ordering, and resource allocation as optimization problems that can be tackled by hybrid quantum–classical algorithms. Using a conceptual model, I map smart contract execution to cost functions suitable for the Quantum Approximate Optimization Algorithm (QAOA) and the Variational Quantum Eigensolver (VQE). I then compare, at a qualitative level, how these quantum-inspired approaches differ from classical heuristics in terms of expected throughput, latency, and cost. A focused literature review on quantum computing, blockchain scalability, and quantum-safe cryptography provides context for these ideas. The results suggest that quantum-enhanced optimization could reduce gas fees, improve transaction scheduling, and support more efficient consensus under heavy load. The project also discusses the need for post-quantum security so that future quantum computers do not undermine blockchain trust. Overall, the work outlines how quantum computing might contribute to faster, safer, and more sustainable automated financial systems.

Next generation.Nov 16, 20250 citations

Designing Quantum-Resilient Blockchain Frameworks: Enhancing Transactional Security with Quantum Algorithms in Decentralized Ledgers

Meenal R Kale, Yousef A. Baker El–Ebiary, L. Sathiya +4 more

Quantum computing is progressing at a fast rate and there is a real threat that classical cryptographic methods can be compromised and therefore impact the security of blockchain networks. All of the ways used to secure blockchain like Rivest–Shamir–Adleman (RSA), Elliptic Curve Cryptography (ECC) and Secure Hash Algorithm 256-bit (SHA256) are the characteristic of the traditional cryptographic techniques vulnerable to attack by quantum algorithms: Shor’s and Grover’s algorithms: can efficiently break asymmetric encryption and speed up brute force attacks. Because of this vulnerability, there exists a need to develop an advance quantum resilient blockchain framework to protect the decentralized ledgers from the future threats of the quantum. This research proposes Post-Quantum Cryptography (PQC), Quantum Key Distribution (QKD) and Quantum Random Number Generation (QRNG) as a formidable architectural integration, to fortify security of blockchain. Classical encryption is replaced with PQC, QKD with secure key exchange by detecting eavesdropping, and QRNG with improving cryptographic randomness to remove the predictable key vulnerability. Only with a small loss of transaction efficiency, we increase transaction encryption accuracy, key exchange security, and resistance to quantum attacks. In this quantum enhanced blockchain design, the idea is to preserve the decentralization, transparency and security and at the same time overcome the future quantum threat. By going through rigorous analysis and comparative evaluation, we demonstrate that the approach saves blockchain networks from the emerging quantum risks to make sure that the decentralized finance, smart contracts and cross chain transactions.

International Journal of Advanced Computer Science and ApplicationsJan 1, 20253 citations

Quantum-Enhanced Blockchain Architecture: Exploring Security and Scalable High Performance

Odnala Srinivas, Sribidhya Mohanty, Nihar Ranjan Pradhan

This paper presents a quantum-enhanced blockchain architecture addressing the dual challenges of quantum vulnerability and scalability limitations in conventional distributed ledgers. We propose a novel framework integrating three key innovations the NIST-standardized Dilithium lattice-based cryptosystem for post-quantum encryption, quantum-resistant binary data structures (1011011 sequences) for integrity verification, and sharded post-quantum key management. Our experimental results demonstrate significant improvements over classical systems, achieving 2,542 TPS throughput (2.7× increase) and reducing cryptographic latency by 67% using BB84 quantum protocols. The architecture provides comprehensive protection against Shor’s and Grover’s algorithms while maintaining blockchain’s decentralized principles through a hybrid quantum-classical consensus mechanism. Comparative analysis reveals our solution outperforms both RSA (classical) and Kyber (hybrid) in all evaluated metrics, including encryption speed (325 MB/s) and key generation time (112 ms). This work establishes a practical pathway for transitioning blockchain infrastructures to quantum-resistant paradigms without compromising performance.

International Conference on Artificial Intelligence and Signal Processing (AISP)Nov 22, 20251 citation

Hybrid Quantum Approximate Optimization Algorithm (HQAOA) for Efficient Blockchain Transaction Scheduling

Soumyadip Paul, Sarit Chakraborty

Quantum technology offers a transformative approach to solving complex computational challenges in decentralized systems, particularly in blockchain transaction scheduling. Efficient transaction scheduling is critical in distributed ledger systems, which often face challenges like dynamic transaction loads. This work proposes a novel approach namely Hybrid Quantum Approximate Optimization Algorithm (HQAOA) which combines Multi-Agent QAOA (MA-QAOA) and Adaptive Layer QAOA (AL-QAOA) to provide a robust solution to such issues. HQAOA leverages a decentralized optimization framework where multiple agents, each representing a node in the network, optimize local transaction scheduling while considering global constraints. Additionally, HQAOA adapts to varying transaction loads by dynamically adjusting the number of quantum layers for each agent, ensuring computational efficiency under different conditions. Such dynamic layer adjustment mechanisms mitigate the adverse effects of quantum noise and ensures optimal performance in scenarios with fluctuating transaction loads. In contrast to traditional QAOA, which struggles with noise and scaling issues, HQAOA provides improved performance by balancing the complexity of the problem with available quantum resources. Experimental results signify the future potential of HQAOA to outperform QAOA, particularly in noisy environments and irregular transaction conditions. This work demonstrates the potential of HQAOA to optimize blockchain transaction scheduling in decentralized systems.

International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC)Feb 27, 20252 citations

Quantum Enhanced Blockchain Legal Intelligence: a Framework for Probabilistic Evidence Evaluation and Secure Sentencing Optimization

Anand Singh Rajawat, Mohammad Zunnun Khan, Mahmoud Khalifa +3 more

This paper introduces a Quantum and Blockchain Integrated Legal Intelligence Framework (QBLIF) for the probabilistic assessment of evidence and the optimization of sentencing in computational jurisprudence. The proposed Quantum Probabilistic Sentencing Optimization Algorithm (QPSOA) employs quantum amplitude estimation and variational quantum circuits to enhance Bayesian evidence aggregation and decision uncertainty models. Quantum subroutines can compute likelihoods faster than classical Bayesian networks and reduce inference time by up to 65 %. To ensure data integrity, the framework incorporates a permissioned Hyperledger blockchain layer to securely store evidential data, algorithm parameters, and decision outputs as tamper-evident, using cryptographically signed smart contracts. This blockchain implementation ensures nonrepudiation, transparency, and decentralized verification of all steps involved in judicial inference. The system is optimized at the system level to perform multi-objective functions that balance fairness constraints, moral compliance, and consistency in sentencing, leveraging quantum-enhanced probabilistic reasoning. Simulated legal data experiments demonstrate that the system improves accuracy (92.4 %), bias mitigation, and auditability while maintaining a low latency of 2.7 ms per transaction. With the help of quantum computing and clear blockchain records, QBLIF offers a new way for AI to make legal decisions that guarantee fairness, accountability, and ethical handling of digital justice processes

International Conference on Intelligent Systems in Engineering, Secured Systems and Cybersecurity (ICISESSC)Apr 9, 20260 citations