Abstract
In recent years, several studies proposed privacypreserving algorithms for solving Distributed Constraint Optimization Problems (DCOPs). All of
those studies assumed that agents do not collude.
In this study we propose the first privacy-preserving
DCOP algorithm that is immune to coalitions, under the assumption of honest majority. Our algorithm – PC-SyncBB – is based on the classical
Branch and Bound DCOP algorithm. It offers constraint, topology and decision privacy. We evaluate its performance on different benchmarks, problem sizes, and constraint densities. We show that
achieving security against coalitions is feasible. As
all existing privacy-preserving DCOP algorithms
base their security on assuming solitary conduct
of the agents, we view this study as an essential
first step towards lifting this potentially harmful assumption in all those algorithms