Paper 2023/103
Fair Delivery of Decentralised Randomness Beacon
Abstract
Thesecurityofmanyprotocolssuchasvotingandblockchains relies on a secure source of randomness. Decentralised Randomness Beacon (DRB) has been considered as a promising approach, where a set of participants jointly generates a sequence of random outputs. While the DRBs have been extensively studied, they failed to capture the advantage that some participants learn random outputs earlier than other participants. In time-sensitive protocols whose execution depends on the randomness from a DRB, such an advantage allows the adversary to behave adaptively according to random outputs, compromising the fairness and/or security in these protocols. In this paper, we formalise a new property, delivery-fairness, to quantify the advantage. In particular, we distinguish two aspects of delivery-fairness, namely length-advantage, i.e., how many random outputs an adversary can learn earlier than correct participants, and time-advantage, i.e., how much time an adversary can learn a given random output earlier than correct participants. In addition, we prove the lower bound of delivery-fairness showing optimal guarantee. We further analyse the delivery-fairness guarantee of state-of-the-art DRBs and discuss insights, which, we show through case studies, could help improve delivery-fairness of existing systems to its optimal.
Metadata
- Available format(s)
- Category
- Cryptographic protocols
- Publication info
- Published elsewhere. The 27th International Conference on Financial Cryptography and Data Security (FC’23)
- Keywords
- Decentralised randomness beaconblockchain
- Contact author(s)
-
me @ runchao rocks
jiangshan yu @ monash edu - History
- 2023-01-27: approved
- 2023-01-27: received
- See all versions
- Short URL
- https://ia.cr/2023/103
- License
-
CC BY-SA
BibTeX
@misc{cryptoeprint:2023/103, author = {Runchao Han and Jiangshan Yu}, title = {Fair Delivery of Decentralised Randomness Beacon}, howpublished = {Cryptology {ePrint} Archive, Paper 2023/103}, year = {2023}, url = {https://eprint.iacr.org/2023/103} }