[Resource Topic] 2025/1041: Rubato: Provably Post-Quantum Secure and Batched Asynchronous Randomness Beacon

Welcome to the resource topic for 2025/1041

Title:
Rubato: Provably Post-Quantum Secure and Batched Asynchronous Randomness Beacon

Authors: Linghe Yang, Jian Liu, Jingyi Cui, Guangquan Xu, Yude Bai, Wei Wang

Abstract:

Distributed Randomness Beacons (DRBs) provide secure, unbiased random numbers for decentralized systems. However, existing protocols face critical limitations. Most rely on cryptographic assumptions which are vulnerable to quantum attacks, risking long-term security in asynchronous networks where unbounded delays may allow attackers time to exploit these weaknesses. Many achieve low beacon generation rates, often below 100 beacons per minute in moderate-scale networks (e.g., Spurt IEEE S&P’22), hindering their use in applications requiring high-throughput randomness. Additionally, traditional Verifiable Secret Sharing (VSS)-based DRBs, using a share-consensus-reconstruct paradigm, are unsuitable for asynchronous networks due to circular dependencies between beacon generation and consensus. Given these limitations, we propose Rubato, the first provably post-quantum secure DRB for asynchronous environments, incorporating a lattice-based batched Asynchronous Verifiable Secret Sharing scheme (bAVSS-PQ). Rubato supports batching of \mathcal{O}(\lambda^2) secrets with communication complexity \mathcal{O}(\lambda n^3 \log n) and tolerates Byzantine faults in up to one-third of the nodes. Integrated with DAG-based consensus protocols like Bullshark or Tusk, its epoch-staggered architecture resolves circular dependencies, enabling efficient and secure randomness generation. Evaluations across 10 to 50 nodes show Rubato generates 5200 to 350 beacons per minute with per-beacon latencies of 11.60 to 96.37 milliseconds, achieving a consensus throughput of 186,088 transactions per second with a latency of 16.78 seconds at 30 nodes. Rubato offers robust post-quantum security and high performance for small-to-medium-scale decentralized systems.

ePrint: https://eprint.iacr.org/2025/1041

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