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Rubayat Khan

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Open access Aug 2026

Quantum Threats to Bitcoin, Cryptocurrency and Blockchain

Objective The authors evaluated how quantum computing threatens the cryptographic primitives used in Bitcoin and other blockchain systems. These findings were translated into a standards-aligned post-quantum migration profile for healthcare ledgers, including consent, identity, provenance, audit, and encrypted off-chain data exchange. Methodology Narrative analysis, theoretical security analysis, and healthcare-oriented deployment mapping of classical public-key and hash primitives used in blockchain protocols were paired with an implementation-oriented migration profile based on finalized National Institute of Standards and Technology (NIST) post-quantum standards. We summarize the mathematical assumptions underlying RSA, Elliptic Curve Cryptography/Elliptic Curve Digital Signature Algorithm (ECC/ECDSA), and Secure Hash Algorithm (SHA-2/SHA-3-family) hash functions; analyze their susceptibility to Shor’s and Grover’s quantum algorithms; compare Federal Information Processing Standards (FIPS) 203 Module-Lattice-Based Key-Encapsulation Mechanism Standard (ML-KEM), FIPS 204 Module-Lattice-Based Digital Signature Standard (ML-DSA), and FIPS 205 Stateless Hash-Based Digital Signature Standard (SLH-DSA); and map their distinct roles to healthcare-ledger authorization, auditability, identity, and encrypted off-chain exchange. The term Advanced Hybrid Module-LWE & Code-Based (AHMC) is used only as shorthand for a standards-aligned hybrid post-quantum cryptography (PQC) migration profile and does not denote a proprietary product, a novel algorithm, or a new cryptographic primitive. Proposed adoption of hybrid, quantum-resistant cryptographic primitives for cryptocurrency wallets, transaction signatures, and ledger security during an interim migration period (hybrid classical + PQC, followed by PQC-only). Qualitative and implementation-oriented assessment of (1) break feasibility of RSA/ECC under Shor’s algorithm, (2) effective security reduction for hash functions under Grover’s algorithm, (3) security assumptions and composition requirements of a standards-aligned hybrid migration profile, (4) transaction-size and verification-cost impact, and (5) healthcare-specific implications for long-retention consent, identity, provenance, and audit records. Results Shor’s algorithm reduces integer factorization and discrete logarithms to polynomial time, directly compromising Rivest–Shamir–Adleman (RSA) and ECC/ECDSA once fault-tolerant, large-scale quantum computers exist. Grover’s algorithm yields a quadratic speedup for brute-force search, effectively halving the security margin of symmetric keys and hash functions at fixed output sizes. The AHMC-L1/L3/L5 profiles use ML-KEM-512/768/1024 for key establishment and ML-DSA-44/65/87 for transaction authentication, with SLH-DSA as a hash-based fallback. During a hybrid ECDSA+PQC migration, verification requires one classical and one PQC verification per authorization; transaction-size overhead is dominated by PQC signatures, approximately 2.4 KB for ML-DSA-44, 3.3 KB for ML-DSA-65, and 4.6 KB for ML-DSA-87 before script and encoding overhead. For healthcare ledgers, these findings support selective use of post-quantum signatures for: high-value state transitions, one-time public-key registration where possible, and continued off-chain storage of protected health information. Deployment suitability remains contingent on workflow-specific latency, storage, availability, key lifecycle, and side-channel testing. Conclusions Quantum risk to blockchain signatures has direct implications for healthcare systems that depend on long-lived consent, identity, provenance, and audit records. A staged, standards-aligned migration profile can preserve authorization and ledger verifiability while keeping protected health information off-chain. The AHMC label refers only to this migration profile, not to a new cryptographic primitive; healthcare adoption requires open implementations, empirical benchmarking, crypto-agile key governance, and side-channel-resistant engineering.

Rubayat Khan, Mazharul Karim, D. Roosan · 0 citations
Conference Open access 2026

Quantum Kernel Support Vector Machine for Quantum Dot State Recognition

: Semiconductor quantum dot platforms require rapid recognition of charge states during automated device tuning, especially when labeled data are scarce and device-to-device variation is strong. This study evaluated state recognition from 100 by 100 two-gate current maps using 30 by 30 labeled patches under a strict device-level split. Patch features were transformed with a signed logarithmic scale, standardized, compressed to four principal components, and scaled to the interval from zero to two pi. A fidelity quantum kernel support vector machine implemented in IBM Qiskit with a four-qubit ZZFeatureMap was compared against linear and radial basis function support vector machines across few-shot budgets of 10, 20, 40, and 80 samples per class. At 80 samples per class, the quantum kernel model achieved accuracy and macro F1 near 0.947 on held-out devices, outperforming the classical baselines in the evaluated setting. Noise-injection experiments showed stable macro F1 under perturbation. These findings support fidelity-based quantum kernels as practical components for automated quantum dot tuning pipelines requiring few-shot generalization.

M. Ashakin, Rubayat Khan, A. Mahata et al. · 0 citations

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