A Case-Based Evaluation of Quantum-Resistant Data Indexing Techniques for Blockchain Databases

Abstract

Blockchain architectures make extensive use of authenticated indexing structures, such as the Merkle Tree, for integrity and efficient retrieval of the data.    However, the advent of quantum computing, in particular, through the use of Shor's and Grover's algorithms, poses a threat to classical cryptographic primitives (RSA, ECDSA, and SHA-256) on which these systems rely. While Post-Quantum Cryptography (PQC) is a solution, its integration introduces significant computational and storage overheads in terms of computation and storage, which remain underexplored in practical database environments. This research has a case study-based assessment of quantum-resistant indexing techniques in a simulated healthcare environment. This research compares a classical baseline using a private Go-Ethereum network against a custom Cryptographic Stress Test Engine modeling NIST-standardized PQC algorithms: Dilithium3 (Lattice-based), XMSS (Stateful Hash-based), and SPHINCS+ (Stateless Hash-based). Experiments were performed on a dataset of 10,000 Electronic Health Records (EHR) using resource-limited hardware to simulate a deployment in a developing infrastructure. Empirical findings show a crucial "storage explosion" in designs that are resistant to quantum computing. The classical ledger was 1.2 MB in size, the Dilithium3 increases storage by approximately 50× (1.2 MB to 62.8 MB) and SPHINCS+ by 270x (up to 325.9 MB).  In terms of indexing latency, Dilithium3 was a nice middle ground option (13.10s), while SPHINCS+ exhibits higher computational cost (25.63s). The study concludes that stateless hash-based schemes are suitable for long-term archival security applications (e.g., degree verification) and lattice-based structures are more suitable for high-throughput systems, such as in real-time healthcare monitoring and national digital currencies.