Bayesian Network-Based Extension for PGP — Estimating Petition Support
Silaghi, Marius (Florida Institute of Technology) | Qin, Song (Florida Institute of Technology) | Matsui, Toshihiro (Nagoya Institute of Technology) | Yokoo, Makoto (Kyushu University)
Consider the problem of estimating the expected number of distinct eligible voters among the authors of a set of electronic signatures gathered for a petition (or citizen initiative) that has to pass legally required thresholds. We formalize this problem and propose an extension to the Pretty Good Privacy Web Of Trust, a mechanism for reciprocally certifying identities between peers. The extension (a) enables agents to certify additional relevant statements about others, and (b) gives agents opportunities for negative authentication statements (e.g., on ineligibility of an identity). A Bayesian Network model enables inferences on the data provided by the proposed PGP extension. Simulations and an agent-based platform are used to validate the concepts.
May-8-2016