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

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, puts the classical cryptographic primitives (RSA, ECDSA, SHA-256) on which these systems are based at risk. While Post-Quantum Cryptography (PQC) is a solution, its integration brings about large overheads in terms of computation and storage, which are not much explored 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 (i.e. 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 Electronic Health Records (EHR) using resource limited hardware to simulate a deployment in developing infrastructure. Empirical findings show a crucial "storage explosion" in designs that are resistant to quantum computing. While the classical ledger was only 1.2 MB in size, the lattice-based Dilithium3 led to a 50x increase in storage requirement (62.8MB) and the stateless SPHINCS+ increased the storage requirement by 270x (325.9MB). In terms of indexing latency, Dilithium3 was a nice middle ground option (13.10s), while SPHINCS+ was computationally expensive (25.63s). The study concludes that stateless hash-based schemes provide long-term security for archive purposes (e.g., degree verification) and lattice-based structures are the only possible solution for high throughput systems such as in real-time healthcare monitoring and national digital currencies.