On a decentralized trustless pseudo-random number generation algorithm

We construct an algorithm that permits a large group of individuals to reach consensus on a random number, without having to rely on any third parties. The algorithm works with high probability if there are less than 50% of colluding parties in the group. We describe also some modifications and generalizations of the algorithm

Auditable Blockchain Randomization Tool

Randomization is an integral part of well-designed statistical trials, and is also a required procedure in legal systems. Implementation of honest, unbiased, understandable, secure, traceable, auditable and collusion resistant randomization procedures is a mater of great legal, social and political importance. Given the juridical and social importance of randomization, it is important to develop procedures in full compliance with the following desiderata: (a) Statistical soundness and computational efficiency; (b) Procedural, cryptographical and computational security; (c) Complete auditability and traceability; (d) Any attempt by participating parties or coalitions to spuriously influence the procedure should be either unsuccessful or be detected; (e) Open-source programming; (f) Multiple hardware platform and operating system implementation; (g) User friendliness and transparency; (h) Flexibility and adaptability for the needs and requirements of multiple application areas (like, for example, clinical trials, selection of jury or judges in legal proceedings, and draft lotteries). This paper presents a simple and easy to implement randomization protocol that assures, in a formal mathematical setting, full compliance to the aforementioned desiderata for randomization procedures

On a decentralized trustless pseudo-random number generation algorithm

We construct an algorithm that permits a large group of individuals to reach consensus on a random number, without having to rely on any third parties. The algorithm works with high probability if there are less than 50 of colluding parties in the group. We describe also some modifications and generalizations of the algorithm