P2P Decentralized Population Census

We describe a framework and investigate techniques for running decentralized census processes that enable observers to independently verify governmental data. Census is a process impacting important issues such as the amount of funding that a community will get from a central government and its representation in the Congress. Correct census is essential for detecting vote stuffing. Census has been historically run by governments, but citizens and NGOs need to be able to verify it. Classical census is expensive and beyond the reach of these players, hence the need for affordable citizen-driven census technology. Various citizens have different opinions as to what information should be gathered and what makes a person eligible to be accounted for in statistics. Using as inputs the official preferences of a given government should enable the verification of the data of that government. The reported work formalizes this problem and introduces a framework and techniques for running a fully decentralized citizen-driven census based on peer-to-peer technology. An addressed challenge is to quantify the uncertainty and the trust in the data provided by P2P users, as well as to develop techniques for reducing this uncertainty. We report on techniques to reason and to extract census-related conclusions based on the available data. Probabilistic models with various approximations are experimented for evaluating the census results in this context.