Recommending the Most Encompassing Opposing and Endorsing Arguments in Debates

Arguments are essential objects in DirectDemocracyP2P, where they can occur both in association with signatures for petitions, or in association with other debated decisions, such as bug sorting by importance. The arguments of a signer on a given issue are grouped into one single justification, are classified by the type of signature (e.g., supporting or opposing), and can be subject to various types of threading. Given the available inputs, the two addressed problems are: (i) how to recommend the best justification, of a given type, to a new voter, (ii) how to recommend a compact list of justifications subsuming the majority of known arguments for (or against) an issue. We investigate solutions based on weighted bipartite graphs.Comment: 10 pages. This report was reviewed by a committee within Florida Tech during April 2014, and had been written in Summer 2013 by summarizing a set of emails exchanged during Spring 2013, concerning the DirectDemocracyP2P.net syste

An efficient way to access an array at a secret index

We propose cryptographic primitives for reading and assigning the (shared) secret found at a secret index in a vector of secrets. The problem can also be solved in constant round with existing general techniques based on arithmetic circuits and the ``equality test\u27\u27 in [Damgard.et.al 05]. However the proposed technique requires to exchange less bits. The proposed primitives require a number of rounds that is independent of the size N of the vector, and only depends (linearly) on the number t of computing servers. A previously known primitive for reading a vector at a secret index works only for 2-party computations. Our primitives work for any number of computing participants/servers. The proposed techniques are secure against passive attackers, and zero knowledge proofs are provided to show that exactly one index of the array is read/written. The techniques work both with multiparty computations based on secret sharing and with multiparty computations based on threshold homomorphic encryption

Secure Stochastic Multi-party Computation for Combinatorial Problems and a Privacy Concept that Explicitely Factors out Knowledge about the Protocol

High levels of security often imply that the computation time should be independent of the value of involved secrets. When the expected answer of the solver is either a solution or unsatisfiable, then the previous assumption leads to algorithms that take always the computation time of the worst case. This is particularly disturbing for NP-hard combinatorial problems. In this work we start from the observation that sometimes (specially for hard problems) users find it acceptable to receive as answer either a solution, the answer unsatisfiable or a failure with meaning don\u27t know. More exactly users accept incomplete solvers. As argued in [Silaghi,Flairs 05], for certain problems privacy reasons lead users to prefer having an answer meaning don\u27t know even when the secure multi-party computation could have proven unsatisfiable (to avoid revealing that all alternatives are infeasible). While the solution proposed there is slower than complete algorithms, here we show secure stochastic solutions that are faster than complete solvers, allowing to address larger problem instances. Two new refined concepts of privacy are introduced, namely \u27requested t-privacy\u27 that factors out treatment of knowledge of the protocol in t-privacy, and a slightly weaker version called \u27non-uniform requested t-privacy\u27. In the last section we discuss arithmetic circuits for complete and stochastic solutions to constraint optimization problems