Library Application for a Fair, Traceable, Auditable and Participatory Drawing Tool for Legal Systems

Abstract

Several applications require random sampling to be protected against a biased behavior. When conflicting parties have different interests in its result, the system must guarantee that collusion among any number of entities cannot influence the resulting computation. Such is the case of legal systems, in which jurors and judges must be randomly picked to ensure impartiality in judicial cases. However, when informational systems are used to generate randomness, it should also provide auditability of its mechanisms to promote confidence in its fairness. This article presents a tool of one such mechanism that combines the randomness provided by hash functions with active social engagement. Each stakeholder in a legal proceeding contribute with his/her own share to the drawing, so that fairness is achieved if at least one entity is honest. Any interested party can audit a drawing using only public information, and misconduct of any party can be traced back to the culprit as soon as the result is computed. Our open-source implementation provides security by design, not depending on the secrecy of its component to attain all the required security properties.