Assessing the Impact of Post-Quantum Digital Signature Algorithms on Blockchains

1. Problem Statement

The advent of quantum computing poses an existential threat to current blockchain security. Traditional cryptographic algorithms, specifically ECDSA (used in Bitcoin and Ethereum) and RSA, are vulnerable to Shor's algorithm, which could allow quantum computers to derive private keys from public keys.

• The Gap: While the National Institute of Standards and Technology (NIST) has standardized several Post-Quantum Cryptography (PQC) algorithms (e.g., ML-DSA, SLH-DSA), there is insufficient empirical data regarding their computational overhead and practical feasibility within the specific constraints of blockchain environments.
• The Question: Can blockchain systems migrate to PQC digital signatures without incurring prohibitive performance penalties that would degrade network throughput or block verification times?

2. Methodology

The authors developed a comprehensive evaluation framework called PQCinBlock to benchmark PQC algorithms against traditional ECDSA in both isolated and simulated blockchain contexts.

A. Experimental Setup

• Hardware/Software Diversity: Experiments were conducted across three distinct environments to ensure robustness:
  • Laptop (ARM): Apple M1 (macOS).
  • Laptop (x64): Intel Core i7-1360P (Ubuntu).
  • Desktop: AMD Ryzen 7 5800X (Ubuntu).
• Algorithms Evaluated:
  • Baseline: ECDSA (P-256, P-384, P-521).
  • PQC Candidates: ML-DSA (formerly Dilithium), Falcon, Mayo, SLH-DSA (formerly SPHINCS+), and Cross.
  • Security Levels: Evaluated across NIST security levels 1, 2, 3, and 5 (Level 4 had no proposals).
• Metrics:
  • Micro-benchmarks: Key generation, Signing, and Verification times (measured in milliseconds).
  • Macro-simulation: Impact on block verification time within simulated Bitcoin and Ethereum networks using the BlockSim framework.
• Scale: Over 31,000 runs per algorithm variant, including 1,000 warm-up iterations and 10,000 measured executions per variant, plus 1,000 blockchain simulations.

B. Workflow

1. Algorithm Benchmarking: Measuring isolated cryptographic operations using liboqs (for PQC) and cryptography (for ECDSA).
2. Blockchain Simulation: Modeling the integration of these algorithms into block verification processes for Bitcoin and Ethereum.
3. Data Consolidation: Aggregating results into statistical datasets (mean, standard deviation) and visualizing performance trade-offs.

3. Key Contributions

1. Comprehensive Benchmarking: The study provides the most extensive comparison to date, covering 7 algorithm families and 62 implementations across multiple hardware architectures (ARM/x64) and operating systems.
2. Blockchain-Specific Simulation: Unlike prior works that focus solely on isolated cryptographic performance, this paper simulates the actual impact on block verification in major blockchain networks (Bitcoin/Ethereum).
3. Open-Source Tooling: The authors released PQCinBlock, a modular, open-source Python tool that orchestrates benchmarking and simulation, allowing for the easy integration of future PQC candidates.
4. Reproducibility: All datasets, code, and experimental parameters are publicly available to foster further research.

4. Key Results

The findings challenge the assumption that PQC will inevitably cause severe performance degradation in blockchains.

A. Isolated Algorithm Performance

• ML-DSA (Dilithium): Demonstrated superior performance to ECDSA in most scenarios, particularly at higher security levels.
  • Example: On an ARM laptop at Security Level 5, ML-DSA verification took 0.14 ms, compared to 0.88 ms for ECDSA (a ~84% reduction).
  • At Level 5 on x64, ML-DSA verification was 0.05 ms vs. ECDSA's 0.31 ms.
• Mayo: Showed competitive performance, often outperforming ECDSA in verification at Levels 1 and 3, though key generation was slower.
• SPHINCS+ (SLH-DSA) & Cross: Generally exhibited higher computational overhead and slower execution times compared to ECDSA and ML-DSA, making them less suitable for high-throughput blockchain applications in their current forms.
• Falcon: Showed fast verification but suffered from extremely slow key generation (seconds vs. milliseconds for others).

B. Blockchain Simulation Impact

• Block Verification: In simulated Bitcoin and Ethereum networks, ML-DSA and Mayo consistently outperformed ECDSA across all security levels.
  • Bitcoin (Desktop, Level 3): ML-DSA reduced block verification time to 63.63 ms, compared to 687.60 ms for ECDSA (a ~90% reduction).
  • Ethereum (Desktop, Level 5): ML-DSA verification was 7.65 ms vs. ECDSA's 51.80 ms.
• Security vs. Performance: Contrary to the trend where higher security levels usually imply slower performance, ML-DSA maintained or improved speed even at Level 5 compared to ECDSA at Level 1.

5. Significance and Limitations

Significance

• Feasibility of Migration: The study proves that migrating from ECDSA to specific PQC algorithms (specifically ML-DSA) is computationally feasible and may even enhance verification efficiency in blockchain systems, provided the network can handle larger data sizes.
• Future-Proofing: It validates that blockchain networks can adopt quantum-resistant security without sacrificing the speed required for consensus and transaction processing.

Limitations & Trade-offs

• Data Size Overhead: While computation is faster or comparable, PQC keys and signatures are significantly larger than ECDSA (except for SLH-DSA, which has similar key sizes).
  • Larger signatures increase transaction size, potentially reducing the number of transactions per block.
  • This could increase latency for consensus and reduce overall network throughput, a factor not fully quantified in the computational benchmarks but acknowledged as a critical constraint.
• Scope: The study focused on Digital Signatures (ECDSA/ML-DSA) and did not evaluate Key Encapsulation Mechanisms (KEM) or RSA. It also focused on general-purpose hardware rather than constrained IoT devices.

Conclusion

The paper concludes that ML-DSA is a prime candidate for immediate adoption in blockchain systems due to its superior performance and verification speed compared to ECDSA, even at high security levels. While storage constraints (larger key/signature sizes) remain a challenge for network throughput, the computational barrier to entry for post-quantum blockchains is lower than previously anticipated.