Economic Security of VDF-Based Randomness Beacons: Models, Thresholds, and Design Guidelines

Researchers Zhenhang Shang and Kani Chen have published a groundbreaking paper titled 'Economic Security of VDF-Based Randomness Beacons: Models, Thresholds, and Design Guidelines' (arXiv:2604.04744). The work challenges the cryptographic-only analysis of Verifiable Delay Functions (VDFs), which are used to generate random numbers for blockchains and distributed systems. The authors argue that real-world attackers are economically motivated, not just cryptographic entities, and can profit by purchasing faster hardware to 'grind' through possible outcomes during the VDF delay period, especially to capture lucrative rewards like MEV (Maximal Extractable Value).

By modeling the attacker as a rational agent facing hardware speedup costs, operating expenses, and stochastic rewards, the researchers cast the attack decision as an optimal-stopping problem. Their analysis proves optimal behavior has a monotone threshold structure, yielding tight conditions that relate system delay parameters to adversarial costs and reward distributions. Using realistic cloud costs, hardware benchmarks, and MEV data, they demonstrate that many proposed VDF delays—often just a few seconds—are economically insecure under plausible conditions.

The paper extends the framework to analyze grinding, selective abort, and multi-adversary competition, showing how each scenario amplifies effective rewards and increases the required delays for security. As a practical solution, the authors introduce deployable guidelines and the concept of Economically Secure Delay Parameters (ESDPs). These ESDPs provide a principled method for system designers to select parameters that ensure security against rational, profit-seeking adversaries, moving beyond purely cryptographic guarantees.