Measuring vote privacy, revisited
David Bernhard, Véronique Cortier, Olivier Pereira, Bogdan Warinschi · 2012
We propose a new measure for privacy of votes. Our measure relies on computational conditional entropy, an extension of the traditional notion of entropy that incorporates both information-theoretic and computational aspects. As a result, we capture in a unified manner privacy breaches due to two orthogonal sources of insecurity: combinatorial aspects that have to do with the number of participants, the distribution of their votes and published election outcome as well as insecurity of the cryptography used in an implementation.