A Verifiable Multiparty Computation Solver for the Assignment Problem and Applications to Air Traffic Management

Abstract

The assignment problem is an essential problem in many application fields and frequently used to optimize resource usage. The problem is well understood and various efficient algorithms exist to solve the problem. However, it was unclear what practical performance could be achieved for privacy preserving implementations based on multiparty computation (MPC) by leveraging more efficient solution strategies than MPC based simplex solvers for linear programs. We solve this question by implementing and comparing different optimized MPC algorithms to solve the assignment problem for reasonable problem sizes. Our empirical approach revealed various insights to MPC based optimization and we measured a significant (50x) speedup compared to the known simplex based approach. Furthermore, we also study the overhead introduced by making the results publicly verifiable by means of non-interactive zero-knowledge proofs. By leveraging modern proof systems we also achieve significant speedup for proof and verification times compared to the previously proposed approaches as well as compact proof sizes.

On the Security of Offloading Post-Processing for Quantum Key Distribution

“…However, for the QKD use case with block sizes k in the range from 10 4 to 10 6 bits and high error rates, the formulation would lead to a relatively large simplex tableau. Very low rates can be expected for this solution approach, given the measured performance for MPC-based LP solving reported in [40].…”